English中文
PUT AI TO WORK
June 18-21, 2019
Beijing, CN

Tuesday, 2019-06-18

09:00

Add to your personal schedule
09:00–17:00 Tuesday, 2019-06-18
2天培训 (2-day Training)
Location: 多功能厅6A+B (Function Room 6A+B)
Rich Ott (The Data Incubator)
PyTorch is a machine learning library for Python that allows users to build deep neural networks with great flexibility. Rich Ott introduces you to the PyTorch workflow and explores how its easy-to-use API and seamless use of GPUs makes it a sought-after tool for deep learning. Join in to get the knowledge you need to build deep learning models using real-world datasets. Read more.
Add to your personal schedule
09:00–17:00 Tuesday, 2019-06-18
2天培训 (2-day Training)
与人工智能交互 (Interacting with AI)
Location: 多功能厅5A+B(Function Room 5A+B)
Season Yang (McKinsey & Company)
Average rating: *****
(5.00, 1 rating)
The TensorFlow library contains computational graphs with automatic parallelization across resources, which is ideal architecture for implementing neural networks. Season Yang introduces TensorFlow's capabilities in Python, and you'll then get your hands dirty building machine learning algorithms piece by piece while using the Keras API provided by TensorFlow with several hands-on applications. Read more.
Add to your personal schedule
09:00–17:00 Tuesday, 2019-06-18
2天培训 (2-day Training)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 多功能厅2(Function Room 2)
Jike Chong (Tsinghua University | Acorns), 黄铃 (Tsinghua University), 陈薇 (排列科技)
您想了解金融企业是怎样利用大数据和人工智能技术来画像个人行为并检测欺诈用户的吗?互联网金融幕后的量化分析流程是怎么杨的?个人信用是怎样通过大数据被量化的?在实践过程中,机器学习算法的应用存在着哪些需要关注的方面?怎样通过图谱分析来融合多维数据,为我们区分正常用户和欺诈用户? 这套辅导课基于清华大学交叉信息研究院开设的一门"量化金融信用与风控分析”研究生课。其中会用LendingClub的真实借贷数据做为案例,解说一些具体模型的实现。 Read more.

10:30

10:30–11:00 Tuesday, 2019-06-18
Location: 1st Floor Foyer
Morning Break (30m)

12:30

12:30–13:30 Tuesday, 2019-06-18
Location: 彩虹厅 (Rainbow Room)
Lunch (1h)

15:00

15:00–15:30 Tuesday, 2019-06-18
Location: 1st Floor Foyer
Afternoon Break (30m)

Wednesday, 2019-06-19

08:00

08:00–08:45 Wednesday, 2019-06-19
Location: 1st Floor Foyer
Morning Coffee (45m)

09:00

Add to your personal schedule
09:00–17:00 Wednesday, 2019-06-19
培训 第二天 (Training Day 2)
Location: 多功能厅6A+B (Function Room 6A+B)
PyTorch is a machine learning library for Python that allows users to build deep neural networks with great flexibility. Rich Ott introduces you to the PyTorch workflow and explores how its easy-to-use API and seamless use of GPUs makes it a sought-after tool for deep learning. Join in to get the knowledge you need to build deep learning models using real-world datasets. Read more.
Add to your personal schedule
09:00–17:00 Wednesday, 2019-06-19
培训 第二天 (Training Day 2)
Location: 多功能厅5A+B(Function Room 5A+B)
The TensorFlow library contains computational graphs with automatic parallelization across resources, which is ideal architecture for implementing neural networks. Season Yang introduces TensorFlow's capabilities in Python, and you'll then get your hands dirty building machine learning algorithms piece by piece while using the Keras API provided by TensorFlow with several hands-on applications. Read more.
Add to your personal schedule
09:00–17:00 Wednesday, 2019-06-19
培训 第二天 (Training Day 2)
Location: 多功能厅2(Function Room 2)
您想了解金融企业是怎样利用大数据和人工智能技术来画像个人行为并检测欺诈用户的吗?互联网金融幕后的量化分析流程是怎么杨的?个人信用是怎样通过大数据被量化的?在实践过程中,机器学习算法的应用存在着哪些需要关注的方面?怎样通过图谱分析来融合多维数据,为我们区分正常用户和欺诈用户? 这套辅导课基于清华大学交叉信息研究院开设的一门"量化金融信用与风控分析”研究生课。其中会用LendingClub的真实借贷数据做为案例,解说一些具体模型的实现。 Read more.
Add to your personal schedule
09:00–12:30 Wednesday, 2019-06-19
Alejandro Saucedo (The Institute for Ethical AI & Machine Learning)
Numerous high-profile incidents have proved undesired bias in machine learning a worrying topic. Alejandro Saucedo uses a hands-on example to demystify machine learning bias. You'll automate the loan-approval process for a company and explore key tools and techniques from the latest research that allows you to assess and mitigate undesired bias in machine learning models. Read more.
Add to your personal schedule
09:00–12:30 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
中英文讲话(Presented in Chinese and English)
Location: 报告厅(Auditorium)
Yijing Chen (Microsoft), Dmitry Pechyoni (Microsoft), Angus Taylor (Microsoft), Vanja Paunic (Microsoft), Henry Zeng (Microsoft)
Average rating: *****
(5.00, 2 ratings)
Almost every business today uses forecasting to make better decisions and allocate its resources more effectively. Deep learning has achieved a lot of success in computer vision, text, and speech processing but has only recently been applied to time series forecasting. Join in to learn how and when to apply deep neural networks to time series forecasting. (presented in Chinese and English) Read more.
Add to your personal schedule
09:00–12:30 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
Location: 多功能厅8A+B(Function Room 8A+B)
Zhen Zhao (Intel)
Intel OpenVINO provides a highly optimized cross-platform deep learning deployment and visual AI solution based on various Intel architectures. Join Zhen Zhao as she explains the structure and workflow of the Intel OpenVINO toolkit, optimization methods by asynchronies, heterogeneous computing, low-precision inference, and instruction set acceleration. Read more.
Add to your personal schedule
09:00–12:30 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
实施人工智能 (Implementing AI)
Location: 多功能厅5C(Function Room 5C)
Zhichao Li (Intel), Kai Huang (Intel), Yang Wang (Intel)
Zhichao Li, Kai Huang, and Yang Wang show you how to build and productionize deep learning applications for big data using Analytics Zoo—a unified analytics and AI platform that seamlessly unites Spark, TensorFlow, Keras, and BigDL programs into an integrated pipeline—illustrated though real-world use cases from JD.com, MLSListings, the World Bank, Baosight, and Midea/KUKA. Read more.

10:30

10:30–11:00 Wednesday, 2019-06-19
Location: 1st Floor Foyer
Morning Break (30m)

12:30

12:30–13:30 Wednesday, 2019-06-19
Location: 彩虹厅 (Rainbow Room)
Lunch - sponsored by Intel AI (1h)

13:30

Add to your personal schedule
13:30–17:00 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
人工智能对商业及社会的影响 (Impact of AI on Business and Society), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Chris Butler (IPsoft)
Purpose, a well-defined problem, and trust are important factors to any system, especially those that employ AI. Chris Butler borrows from the principles of design thinking to lead you through exercises that help you create more impactful solutions and better align your team. Read more.
Add to your personal schedule
13:30–17:00 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 报告厅(Auditorium)
Henry Zeng (Microsoft), Lu Zhang (Microsoft), xiao zhang (Microsoft)
Average rating: ****.
(4.00, 3 ratings)
Intelligent experiences powered by AI seem like magic, but developing them is cumbersome, involving a series of time consuming sequential and interconnected decisions along the way. What if you had an automated service that could identify the best machine learning pipelines for your given problem or data? Lu Zhang, Henry Zeng, and Xiao Zhang detail how automated machine learning does that. Read more.
Add to your personal schedule
13:30–17:00 Wednesday, 2019-06-19
3小时辅导课 (3-hour Tutorial)
英文讲话 (Presented in English)
Location: 多功能厅8A+B(Function Room 8A+B)
Richard Liaw (UC Berkeley RISELab), Siyuan Zhuang (UC Berkeley RISELab)
Ray is a general-purpose framework for programming your cluster. Richard Liaw leads a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art AI algorithms. Read more.

15:00

15:00–15:30 Wednesday, 2019-06-19
Location: 1st Floor Foyer
Afternoon Break (30m)

Thursday, 2019-06-20

08:00

08:00–08:45 Thursday, 2019-06-20
Location: 3楼序厅(3rd Floor Foyer)
Morning Coffee (45m)
Add to your personal schedule
08:00–08:30 Thursday, 2019-06-20
活动 (Event)
Location: 3楼序厅(3rd Floor Foyer)
本次人工智能会议上午8:00-8:30可以和希望社交的与会来宾见面。我们将在周五主题演讲之前搞一个非正式快速社交活动。一定记得带名片参加活动。 Read more.

08:45

Add to your personal schedule
08:45–08:50 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ben Lorica (O'Reilly Media), Jason (Jinquan) Dai (Intel), Roger Chen (Computable)
Program chairs Ben Lorica, Jason Dai, and Roger Chen open the first day of keynotes. Read more.

08:50

Add to your personal schedule
08:50–09:05 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ziya Ma walks you through Intel’s scalable data insights strategy and related big data analytics and AI technologies such as Analytics Zoo—an end-to-end analytics and AI pipeline for developing full solutions with Apache Spark on Intel Xeon and Intel Optane DC Persistent Memory at scale. She highlights customers use cases and collaboration with industry leaders throughout. Read more.

09:05

Add to your personal schedule
09:05–09:15 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ben Lorica (O'Reilly Media), Roger Chen (Computable)
Accelerating AI Adoption Read more.

09:15

Add to your personal schedule
09:15–09:20 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Frank Wu (Dell Technologies)
This is the data era. Data helps to make better products and services, allowing a company to attract more customers, which results in more data—and repeat. Eventually, this turns into data capital, the most valuable corporate asset. Frank Wu explains why how you use your data will determine your future. Read more.

09:20

Add to your personal schedule
09:20–09:35 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Long Wang (Tencent)
Average rating: *****
(5.00, 1 rating)
We all know that the cloud is the best place to use new technologies. Long Wang examines what's happening for AI in the cloud: How does AI in the cloud accelerate the innovations in the industry? What's mostly possible? What's still on the way? How does the cloud help? Read more.

09:35

Add to your personal schedule
09:35–09:45 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Eitan Medina (Habana Labs)
Eitan Medina details advances made possible with AI processors designed to address AI-specific computing requirements, chief among them increasing AI throughput speeds while lowering power consumption. This new class of AI processing brings significantly improved productivity and efficiency to the data center to overcome limitations of existing CPU- and GPU-based solutions. Read more.

09:45

Add to your personal schedule
09:45–10:05 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Maria Zhang (LinkedIn)
Average rating: *****
(5.00, 1 rating)
If the most dramatic headlines were true, we’d all be preparing for robots to take over our jobs, our lives, and, eventually, the world. But the truth is, automation and AI are doing more to improve the quality of our work than they are to replace us. Maria Zhang examines AI and its impact on people’s jobs, quality of work, and overall business outcomes. Read more.

10:05

Add to your personal schedule
10:05–10:20 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Pete Warden (Google)
There are over 250 billion embedded devices in the world. On-device machine learning gives us the ability to turn wasted data into actionable information and will enable a massive number of new applications over the next few years. Pete Warden digs into why embedded machine learning is so important, how to implement it on existing chips, and some of the new use cases it will unlock. Read more.

10:20

Add to your personal schedule
10:20–10:40 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ion Stoica (UC Berkeley)
Ion Stoica outlines a few projects at the intersection of AI and systems that RISELab, at the University of California, Berkeley, is developing. RISELab is the successor of AMPLab, where several highly successful open source projects, including Apache Spark and Apache Mesos, were developed. Read more.

10:40

Add to your personal schedule
10:40–10:45 Thursday, 2019-06-20
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ben Lorica (O'Reilly Media), Jason (Jinquan) Dai (Intel), Roger Chen (Computable)
Program chairs Ben Lorica, Jason (Jinquan) Dai, and Roger Chen close the first day of keynotes. Read more.

10:45

10:45–11:15 Thursday, 2019-06-20
Location: 报告厅序厅 (Auditorium Foyer)
Morning Break - Sponsored by Dell Technologies (30m)

11:15

Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Tao Lu (Microsoft), Chenhui Hu (Microsoft)
Average rating: **...
(2.50, 2 ratings)
Forecasting customer activities is an important, common business problem, and Tao Lu and Chenhui Hu forecast customer behavior based on billions of user activities. Join them as they share how Microsoft improved forecasting accuracy by 25% with dilated convolutional neural networks and reduced time in development by 80% with a set of time series forecasting best practices. Read more.
Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
刘怀军 (美团)
该议题的内容包括: 1.外卖个性化场景:个性化搜索,个性化推荐 2.个性化产品形态包括:商家、商品、套餐等 3.外卖个性化中应用的AI技术包括:NLP,DNN,图像技术,强化学习 4.针对外卖业务的特点,介绍个性化场景中,几项重点AI技术的落地、挑战与思考 Read more.
Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
David Low (Pand.ai)
Average rating: *****
(5.00, 1 rating)
Transfer learning has been a tremendous success in computer vision as a result of the ImageNet competition. In the past few months, natural language processing (NLP) has witnessed several breakthroughs with transfer learning, namely ELMo, Transformer, ULMFit, and BERT. Join David Low as he showcases the use of transfer learning on NLP applications with state-of-the-art accuracy. Read more.
Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 英文讲话 (Presented in English)
Location: 多功能厅5A+B(Function Room 5A+B)
Renjei Li (NetEase Fuxi Lab)
Theoretical AI research isn't a bottleneck in AI, but finding a good application scenario for AI is. Renjei Li explains why gaming is a great scenario for AI and walks you through recent research in the future of AI games involving reinforcement learning, natural language processing (NLP), computer vision and graphics, and user personas and virtual humans. Read more.
Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
企业人工智能 (AI in the Enterprise)
Location: 多功能厅6A+B (Function Room 6A+B)
Min Shen (LinkedIn)
Average rating: ****.
(4.00, 1 rating)
领英公司的几乎所有产品都离不开基于海量数据和大规模数据运算的机器学习模型。怎样构建一个稳定,高效,和易用的人工智能基础架构,越来越成为一个核心的问题。 这个演讲会先介绍领英大数据团队是怎样在5年的时间里演进这个基础架构,从开始的完全基于Spark的系统,到现在Spark+TensorFlow的环境。 我们还会重点介绍近期解决的技术挑战,来应对接近500PB数据和将近6亿会员的巨大经济图谱。这些挑战包括大规模重量级的深度学习模型,Spark的调优,以及在机器学习生产线中连接不同的步骤(数据准备,模型构建,模型训练,在线inference)。 最后我们会介绍我们近期一些成功的深度学习案例,以及团队在AI基础架构上未来2~3年的计划和愿景。 Read more.
Add to your personal schedule
11:15–11:55 Thursday, 2019-06-20
40分钟议题 (40-minute session)
英文讲话 (Presented in English)
Location: 多功能厅8A+B(Function Room 8A+B)
Eitan Medina (Habana Labs)
The new class of purpose-built AI processors presents data center engineers and developers with opportunities to deliver tangible advancements in AI productivity and efficiency, resulting in lower total cost of ownership. Eitan Medina reveals the advantages derived from new approaches to building high-performance AI systems. Read more.

11:55

Add to your personal schedule
11:55–13:10 Thursday, 2019-06-20
活动 (Event)
Location: 彩虹厅及国际厅 (Rainbow Room & Ballroom)
午餐时寻找和其他与会者的社交?主题桌会讨论帮助你结识相似行业或有共同话题的与会来宾。 Read more.

13:10

Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
Bas Geerdink (ING)
Average rating: *****
(5.00, 1 rating)
ING is a data-driven enterprise, with analytics skills as a top strategic priority. AI is at the core of ING’s business, and the company is investing in AI, big data, and analytics to improve business processes such as balance forecasting, fraud detection, and customer relation management. Follow along with (and be inspired by) Bas Geerdink's overview of the company's use cases and technology. Read more.
Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 报告厅(Auditorium)
Henry Zeng (Microsoft), Klein Hu (Microsoft), Emma Ning (Microsoft)
An open and interoperable ecosystem enables you to choose the framework that's right for you, train at scale, and deploy to cloud and edge. ONNX provides a common format supported by many popular frameworks and hardware accelerators. Henry Zeng, Klein Hu, and Emma Ning introduce you to ONNX and its core concepts. (Presented in English and Chinese.) Read more.
Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
40分钟议题 (40-minute session)
英文讲话 (Presented in English), 隐私、道德与规范 (Privacy, Ethics, and Compliance)
Location: 多功能厅2(Function Room 2)
Alex Ingerman (Google)
Federated learning involves training ML models across a fleet of participating devices without collecting their data in a central location. Alex Ingerman examines federated learning, compares the traditional and federated ML workflows, and explores the current and upcoming use cases for decentralized machine learning with examples from Google's deployment of this technology. Read more.
Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
Ying Liu (Abakus 鲸算科技(Wecash闪银))
Abakus's AI debt collection platform provides a friendly and humane product solution designed for people who work on the frontline: live agents of the organization. The company's agent training has been enhanced with an AI-friendly culture. Join Ying Liu as she details the results of an experiment showing how the company improved the performance of the collection assistants. Read more.
Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
40分钟议题 (40-minute session)
与人工智能交互 (Interacting with AI), 模型与方法 (Models and Methods)
Location: 多功能厅6A+B (Function Room 6A+B)
姜涛 (Kwai)
介绍如何综合应用多项人工智能技术进行K歌修音和短视频自动配乐,涉及的相关技术包括:人声/音乐分离、高精度的基频提取、自动作曲/作词技术、基于视频内容的音乐生成等。 Read more.
Add to your personal schedule
13:10–13:50 Thursday, 2019-06-20
40分钟议题 (40-minute session)
Location: 多功能厅8A+B(Function Room 8A+B)
Youhui Zhou (Dell)
Average rating: *****
(5.00, 1 rating)
Improve the utilization rate of data center resources. Join in to explore DL infrastructure and a GPU-as-a-service solution. You'll learn how it simplifies the AI compute requirements with automated access, better control, and simplified provisioning all while pushing your GPU resources to the limit accelerating your model training and inference. Read more.

14:00

Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Pete Warden (Google)
Average rating: *****
(5.00, 2 ratings)
Pete Warden explains how to use Google's open source framework to run machine learning models on embedded processors like microcontrollers and DSPs. Discover what you need to get started using the code itself, including hardware, coding tools, and getting the library built. Read more.
Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 报告厅(Auditorium)
Hui Xue (微软亚洲研究院)
人工智能在过去的几年里飞速发展,但是机器学习的实践和应用需要消耗一定的人力和时间。例如,如何去做特征选择,如何设计一个适合该任务的神经网络模型等等。而自动机器学习技术,可以帮助开发者和机器学习实战者,缩短开发周期,提高效率。我们的介绍主要包括:自动机器学习技术的进展;我们开源的自动机器学习开源库neural network intelligence; 如何利用自动机器学习的技术,在产品和应用上提高效率,节省所需的时间和缩短周期。我们会在最后一部分,分享一些利用自动特征选择,自动参数调整以及模型架构搜索上的成功案例。 Read more.
Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
Arun Verma (Bloomberg)
Average rating: ****.
(4.00, 1 rating)
To gain an edge in the markets, quantitative hedge fund managers require automated processing to quickly extract actionable information from unstructured and increasingly nontraditional sources of data. Arun Verma details AI and machine learning (ML) techniques in quantitative finance that lead to profitable trading strategies. Read more.
Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
执行简报/最佳实践 (Executive Briefing/Best Practices)
Location: 多功能厅5A+B(Function Room 5A+B)
杨博理 (宜信大数据创新中心)
AI技术是线上财富管理领域中不可或缺的一环。在这个演讲中,我会将财富管理进一步细分为投资和实现财务目标两个方面,并分别讲解AI技术在这两个细分层面上的应用问题。对于投资而言,一些具备强金融逻辑的变量可能更适合使用机器学习进行预测。而在资产价格的预测上,可以尝试使用AI和大数据技术获取更多的有价值信息。对于实现财务目标而言,基于NLP技术的语义理解、引导式对话是理解用户的关键,基于AI和大数据的KYC也是判断用户状态的有效工具,而一个融合了财务规划、投资和精算知识的专家系统则是定制级规划的核心。 Read more.
Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods)
Location: 多功能厅6A+B (Function Room 6A+B)
peng ni (凡普金科集团有限公司)
该议题主要包括:1. 语音切分技术的原理和应用;2. 语音识别模型的构建优化;3. 语音情感分析构建应用;4. 语音数据的实时处理框架;5. 金融场景业务落地。 Read more.
Add to your personal schedule
14:00–14:40 Thursday, 2019-06-20
40分钟议题 (40-minute session)
赞助商赞助 (Sponsored)
Location: 多功能厅8A+B(Function Room 8A+B)
Chen Zhang (Chuang Lin Tech)
浙江创邻科技有限公司创始人张晨将介绍创邻科技自主知识产权的核心技术分布式图数据库Galaxybase。Galaxybase是目前世界上最快、延展性最好的图数据库,比Neo4j快20-100倍,高并发实时读写快1000倍,填补了我国图数据存储及处理领域的空白,并打造了国内首个专注图挖掘的认知计算平台。核心团队由海归大数据专家、国家青年千人、浙江省千人专家、杭州市特聘专家,及国内外名校博士、硕士组成,在海量数据并发并行处理、人工智能、图运算等领域有多项世界领先的技术储备。2018年获得了百度风投BV投资。演讲将介绍图数据库的技术背景、经典应用、Galaxybase的技术、应用和未来的挑战。 Read more.

14:50

Add to your personal schedule
14:50–15:30 Thursday, 2019-06-20
40分钟议题 (40-minute session)
与人工智能交互 (Interacting with AI), 实施人工智能 (Implementing AI), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Mark Ryan (IBM), Alina Zhang (Skylinerunners)
Average rating: *****
(5.00, 1 rating)
Toronto is unique among North American cities for having a legacy streetcar network as an integral part of its transit system. This means streetcar delays are a major contributor to gridlock in the city. Learn about applying deep learning time series forecasting to machine learning as Mark Ryan and Alina Li Zhang explain how streetcar delays can be predicted...and prevented. Read more.
Add to your personal schedule
14:50–15:30 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Tiezhen Wang (Google)
Average rating: *****
(5.00, 2 ratings)
TensorFlow 2.0 is a major milestone with a focus on ease of use. Tiezhen Wang walks you through the new exciting features and best practices. Join in to explore distributed strategies and edge deployment (TensorFlow Lite and TensorFlow.js). Read more.
Add to your personal schedule
14:50–15:30 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
Chenta Lee (IBM)
By combining various analytics including DGA, squatting, tunneling, and rebinding detection, it's possible to build a DNS analytic playbook to anneal actionable threat intelligence from billions of DNS requests. Chenta Lee outlines how DNS volumetric data and analytics complement each other to create a new dimension to look at security postures and how to leverage it in security operations. Read more.
Add to your personal schedule
14:50–15:30 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods)
Location: 多功能厅5A+B(Function Room 5A+B)
Kai Huang (Intel)
Real-time recommender systems are critical for the success of the ecommerce industry. Join Kai Huang, Luyang Wang, and Jing Kong as they showcase how to build efficient recommender systems for the ecommerce industry using deep learning technologies. Read more.
Add to your personal schedule
14:50–15:30 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods)
Location: 多功能厅6A+B (Function Room 6A+B)
Mingxi Wu (TigerGraph)
图数据上的非监督学习在激活大数据的经济价值上有着广泛和不可替代的作用。 PageRank能够发掘重要的实体, 社区发掘(community detection)可以找到具有某种特性的群体,紧密度中心性算法(Closeness Centrality)可以自动找到远离群体的个体。所有这些算法都是非监督的学习。 我们分享一些具体客户案例来展示他们的价值,同时分享怎样在大数据上灵活应用这些开源算法。 Read more.
14:50–15:30 Thursday, 2019-06-20
Location: 多功能厅8A+B(Function Room 8A+B)
TBC

15:30

15:30–16:20 Thursday, 2019-06-20
Location: 报告厅序厅 (Auditorium Foyer)
Afternoon Break (50m)

16:20

Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
人工智能对商业及社会的影响 (Impact of AI on Business and Society), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
David Maman (Binah)
Average rating: *****
(5.00, 1 rating)
Zero-day attacks. IoT-based botnets. Cybercriminal AI versus cyberdefender AI. While these won’t be going away, they aren’t our biggest worry in cybercrime. Hacking humans is. David Maman demonstrates how the combination of minutes of video, signal processing, remote heart-rate monitoring, AI, ML, and data science can identify a person’s health vulnerabilities, which evildoers can make worse. Read more.
Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
人工智能对商业及社会的影响 (Impact of AI on Business and Society)
Location: 报告厅(Auditorium)
温浩 (云从科技)
AI企业发展应该是一个从学术研究、行业验证、商业落地、行业平台到智能生态的一层层深入过程,这也是人工智能企业理想的发展阶段。 云从科技计划打造核心技术闭环,让计算机更好地服务人类。并将全面降低人工智能准入门槛,让“AI普惠”成为可能。 Read more.
Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
Maulik Soneji (GO-JEK), Jewel James (GO-JEK)
Hear how Maulik Soneji and Jewel James prototyped the search framework that personalizes the restaurant search results by using machine learning (ML) to learn what constitutes a relevant restaurant given a user's purchasing history. Read more.
Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
Dongfeng Chen (Clobotics)
Average rating: ****.
(4.00, 1 rating)
One of the biggest challenges to growth remains the high costs of constructing wind farms, as well as the ongoing operations and maintenance costs. Dongfeng Chen dives into the successes and failures of creating an entirely autonomous visual-recognition-powered drone inspection solution for turbine blades, which increased the efficiency by 10 times. Read more.
Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅6A+B (Function Room 6A+B)
Xing Fan (Squirrel AI)
Squirrel AI Learning is the first artificial intelligence technology company in China to apply AI-adaptive technology to K–12 education. Xing Fan dives deep into its implementation approach and teaches you about the business process, pedagogy, architecture, operation, and theoretical underpinning of this adaptive learning service. Read more.
Add to your personal schedule
16:20–17:00 Thursday, 2019-06-20
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅8A+B(Function Room 8A+B)
Shan Yu (Intel)
Average rating: ****.
(4.00, 1 rating)
Using AI to play games is often perceived as an early step toward achieving general machine intelligence, as the ability to reason and make decisions based on sensed information is an essential part of general intelligence. Shan Yu shares lessons learned from her attempts using AI on Spark to play games. Read more.

17:00

Add to your personal schedule
17:00–17:45 Thursday, 2019-06-20
活动 (Event)
Location: 赞助商区域 (Sponsor Pavilion)
周四最后一节分会场议题后请加入我们的赞助商展馆招待会。与其他与会来宾展开社交,同时参观人工智能领域的创新公司。本次活动向所有赞助商、参展商及与会来宾开放。 Come enjoy snacks and beverages with fellow AI Conference attendees, speakers, and sponsors. Read more.

Friday, 2019-06-21

08:00

08:00–08:45 Friday, 2019-06-21
Location: 3楼序厅(3rd Floor Foyer)
Morning Coffee (45m)
Add to your personal schedule
08:00–08:30 Friday, 2019-06-21
活动 (Event)
Location: 3楼序厅(3rd Floor Foyer)
在本次人工智能大会上与寻求联系的与会者会面。会议将在周四主题演讲之前举行一个非正式的快速社交活动。一定要带上自己的名片来享受社交活动。 Read more.

08:45

Add to your personal schedule
08:45–08:50 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ben Lorica (O'Reilly Media), Roger Chen (Computable), Jason (Jinquan) Dai (Intel)
Average rating: *****
(5.00, 1 rating)
Program chairs Ben Lorica, Jason Dai, and Roger Chen open the second day of keynotes. Read more.

08:50

Add to your personal schedule
08:50–09:00 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Abigail Hing Wen (Intel Corp.)
Abigail Hing Wen catches you up on some of the most exciting recent breakthroughs in the industry, including natural language processing strong enough to generate sentences indistinguishable from a human’s, highly accurate 3D protein structure prediction to fight disease, and leaps forward in reinforcement learning, a more natural but very complex alternative to other forms of machine learning. Read more.

09:00

Add to your personal schedule
09:00–09:15 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Haoyuan Li (Alluxio)
Haoyuan Li offers an overview of a data orchestration layer that provides a unified data access and caching layer for single cloud, hybrid, and multicloud deployments. It enables distributed compute engines like Presto, TensorFlow, and PyTorch to transparently access data from various storage systems while actively leveraging an in-memory cache to accelerate data access. Read more.

09:15

Add to your personal schedule
09:15–09:30 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Hao Zheng (PlusAI)
PlusAI is developing a full stack self-driving technology to enable large-scale autonomous commercial fleets. Hao Zheng examines some of the unique challenges across different layers of the technology stack of building an autonomous truck that's both safe and efficient and dives into how PlusAI is addressing them. Read more.

09:30

Add to your personal schedule
09:30–09:45 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Mikio Braun (Zalando SE)
What do your customers want? What are the current and upcoming trends? Mikio Braun takes a look at Zalando and the retail industry to explore how AI is redefining the way ecommerce sites interact with customers to create a personalized experience that strives to make sure customers find what they want when they need it. Read more.

09:45

Add to your personal schedule
09:45–10:00 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Yangqing Jia (Alibaba Group)
Average rating: *****
(5.00, 2 ratings)
The recent years of AI has grown out of labs and created a transformative power for a vast range of industries. But, while we take it for granted that AI and Cloud come hand in hand, I'll show you an argument one step further: AI should be Cloud Native. Read more.

10:00

Add to your personal schedule
10:00–10:20 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Michael James (Cerebras)
Average rating: ****.
(4.00, 1 rating)
Artificial intelligence is defining a new generation of computer technology with applications that blur the boundaries between intuition, art, and science. Michael James examines the fundamental drivers of computer technology, surveys the landscape of AI hardware solutions, and explores the limits of what's possible as new computer platforms emerge. Read more.

10:20

Add to your personal schedule
10:20–10:40 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Tim Kraska (MIT)
Average rating: *****
(5.00, 1 rating)
Systems and applications are composed from basic data structures and algorithms. Most of these have been around since the beginnings of CS and form every intro lecture. Yet, we might soon face an inflection point. Tim Kraska outlines different ways to build learned algorithms and data structures to achieve instance optimality and unprecedented performance for a wide range of applications. Read more.

10:40

Add to your personal schedule
10:40–10:45 Friday, 2019-06-21
主题演讲 (Keynote)
Location: 紫金大厅A(Grand Hall A)
Ben Lorica (O'Reilly Media), Jason (Jinquan) Dai (Intel), Roger Chen (Computable)
Program chairs Ben Lorica, Jason (Jinquan) Dai, and Roger Chen close the second day of keynotes. Read more.

10:45

10:45–11:15 Friday, 2019-06-21
Location: 报告厅序厅 (Auditorium Foyer)
Morning Break (30m)

11:15

Add to your personal schedule
11:15–11:55 Friday, 2019-06-21
40分钟议题 (40-minute session)
英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Joseph Spisak (Facebook)
Average rating: *****
(5.00, 1 rating)
Learn how PyTorch 1.0 enables you to take state-of-the-art research and deploy it quickly at scale in areas from autonomous vehicles to medical imaging. Joseph Spisak dives deep on the latest updates to the PyTorch framework including TorchScript and the JIT compiler, deployment support, and the C++ interface, and explains how Facebook uses PyTorch 1.0 to power AI across its products. Read more.
Add to your personal schedule
11:15–11:55 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Yang Wang (Intel)
Building a model is fun and exciting; putting it to production is a different story. Yang Wang offers an overview of Analytics Zoo, a unified analytics and AI platform for distributed TensorFlow, Keras, and BigDL on Apache Spark, designed for production environments. See how you can benefit from its easy deployment, high performance, and efficient model serving for deep learning applications. Read more.
Add to your personal schedule
11:15–11:55 Friday, 2019-06-21
40分钟议题 (40-minute session)
英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
Roger Chen (Computable)
Roger Chen details how to enable powerful data lineage properties with decentralized data governance models using blockchain technology. As a result, organizations can easily satisfy growing compliance regulations around data privacy while gaining access to rich external data resources for building AI models. Read more.
Add to your personal schedule
11:15–11:55 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
LI YUAN (Perceptin 深圳普思英察科技有限公司)
如何令自动驾驶技术落地并结合新潮传媒以及新零售业务,相关的技术是如何实现,商业模式是什么以及如何通过人工只能技术提升行业的效率。 Read more.
Add to your personal schedule
11:15–11:55 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅6A+B (Function Room 6A+B)
刘祁跃 (爱奇艺)
对视频进行精彩度分析,有助于筛选优质内容,尤其是冷启动阶段 同时,基于算法对精彩内容的理解,可以辅助创作,如进行标题辅助生成、动态/精彩封面生成、智能拆条等 我们通过对视频、音频、文本等多模态内容分析,同时利用用户交互数据,建立了完备的视频精彩度分析系统,并落地在长/短视频的不同业务场景下,明显提升了业务产出质量和效率 Read more.

11:55

Add to your personal schedule
11:55–13:10 Friday, 2019-06-21
活动 (Event)
Location: 彩虹厅及国际厅 (Rainbow Room & Ballroom)
午餐时寻找和其他与会者的社交?主题桌会讨论帮助你结识相似行业或有共同话题的与会来宾。 Read more.

13:10

Add to your personal schedule
13:10–13:50 Friday, 2019-06-21
40分钟议题 (40-minute session)
人工智能对商业及社会的影响 (Impact of AI on Business and Society), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Yue Cathy Chang (TutumGene)
Genome editing has been dubbed a top technology that could create trillion-dollar markets. Learn how recent advancements in the application of AI to genomic editing are accelerating transformation of medicine with Yue Cathy Chang as she explores how AI is applied to genome sequencing and editing, the potential to correct mutations, and questions on using genome editing to optimize human health. Read more.
Add to your personal schedule
13:10–13:50 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Yiheng Wang (Tencent)
Average rating: *****
(5.00, 1 rating)
机器学习项目在企业中实际落地往往涉及到复杂工作流构建和数据管理,以及多种工具的整合。而且随着数据规模的增加,团队规模的扩大,这一任务更具挑战性。Apache Spark是业界流行的大数据框架,被广泛的应用在海量数据的分析处理。本议题将介绍我们在腾讯云上如何基于Apache Spark为客户建立一个一站式机器学习平台的相关工作。主要内容包括多种数据源的接入,构建复杂数据管线,利用数据可视化理解数据,通过可插拔的机制使用各种流行的机器学习框架,以及部署和监控模型。我们也会分享在这一过程中遇到的问题和挑战。听众也可以了解到,通过这种和大数据紧密结合的一站式机器学习,用户可以怎样更加高效的建立和管理他们的机器学习项目,从而加速了机器学习在业务中的落地。 Read more.
Add to your personal schedule
13:10–13:50 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
Mikio Braun (Zalando SE)
Mikio Braun takes you through the past 20 years of machine learning research to explore aspects of artificial intelligence, then examines current examples like autonomous cars and chatbots. Together you'll put together a mental model for a reference architecture for artificial intelligence systems. Read more.
Add to your personal schedule
13:10–13:50 Friday, 2019-06-21
40分钟议题 (40-minute session)
案例研究 (Case Studies)
Location: 多功能厅5A+B(Function Room 5A+B)
Weisheng Xie (China Telecom BestPay Co., Ltd)
Weisheng Xie dives deep into how China Telecom uses adversarial autoencoders (AAEs) for risk factors modeling to fight a special kind of financial fraud. It's just one step in a long path of unsupervised tasks, but it's proved to be efficient and effective in practice. Read more.
Add to your personal schedule
13:10–13:50 Friday, 2019-06-21
40分钟议题 (40-minute session)
模型与方法 (Models and Methods)
Location: 多功能厅6A+B (Function Room 6A+B)
陈玉荣 (Intel)
深度学习在许多领域尤其是视觉识别/理解方面取得了巨大突破,但它在训练和部署方面都存在一些挑战。本讲座将介绍我们通过高效CNN算法设计、领先DNN模型压缩技术和创新部署时DNN网络结构优化来解决深度学习部署挑战的前沿研究成果。 Read more.

14:00

Add to your personal schedule
14:00–14:40 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI), 模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 紫金大厅B(Grand Hall B)
Kaz Sato (Google)
Average rating: *****
(5.00, 1 rating)
Kaz Sato explains how creating an ML model is just a starting point. To bring the technology into production service, you need to solve various real-world issues such as building a data pipeline for continuous training, automated validation of the model, version control of the model, scalable serving infra, and ongoing operation of the ML infra with monitoring and alerting. Read more.
Add to your personal schedule
14:00–14:40 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Chaoguang Li (Qiniu), Bin Fan (Alluxio), Haoyuan Li (Alluxio)
The Atlab Lab at Qiniu Cloud focuses on deep learning for computer vision. Chaoguang Li, Haoyuan Li, and Bin Fan lead a deep dive into AVA, a high-performance and cost-effective cloud-based training platform for deep learning, which deeply integrates an open source software stack including TensorFlow, Caffe, Alluxio, and KODO, the company's own cloud object storage. Read more.
Add to your personal schedule
14:00–14:40 Friday, 2019-06-21
40分钟议题 (40-minute session)
与人工智能交互 (Interacting with AI), 实施人工智能 (Implementing AI)
Location: 多功能厅2(Function Room 2)
Orchlon Ann (Rakuten), TzuLin Chin (Rakuten)
Average rating: ****.
(4.00, 1 rating)
Orchlon Ann and TzuLin Chin offer an overview of the Data Science Platform, a suite of tools for exploring data, training models, and running GPU/CPU compute jobs in an isolated container environment. Discover it's benefits, including one-click machine learning environment creation, a powerful job scheduler, and a flexible function-as-a-service component. Read more.
Add to your personal schedule
14:00–14:40 Friday, 2019-06-21
40分钟议题 (40-minute session)
与人工智能交互 (Interacting with AI), 实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
王书浩 (透彻影像)
病理学是医学诊断的“金标准”,病理报告对于临床医生提供进一步治疗策略至关重要。一位能够独立发病理报告的病理医师需要10年以上的培养周期,我国目前共有约1万名注册在案的病理医师,根据WHO的要求,人才缺口为4-9万人。使用人工智能来辅助病理医师对样本进行诊断,不仅能够大幅提高医师的诊断效率,而且可以减少漏诊,提高诊断准确率。数字化的病理影像能够观察到组织的细胞形态,在最高倍数字扫描时,文件尺寸达到GB量级,需要从人工智能和系统工程的层面去应对这些挑战。在这个演讲中,我们将从人工智能系统的构建方法入手,介绍透彻影像与中国人民解放军总医院在消化道病理影像辅助系统研发过程中的技术细节。同时,我们将分享诊断系统从部署到落地使用的一些经验。 Read more.
Add to your personal schedule
14:00–14:40 Friday, 2019-06-21
40分钟议题 (40-minute session)
模型与方法 (Models and Methods)
Location: 多功能厅6A+B (Function Room 6A+B)
Dingxian Wang (eBay)
In recent years, there's been increasing attention on incorporating knowledge graphs into recommender systems. By exploring the interlinks within a knowledge graph, you can discover the connectivity between users and items as paths. Dingxian Wang outlines a new model, knowledge-aware path recurrent network (KPRN), for exploiting knowledge graphs for recommendation. Read more.

14:50

14:50–15:30 Friday, 2019-06-21
Location: 紫金大厅B(Grand Hall B)
TBC
Add to your personal schedule
14:50–15:30 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Zhenxiao Luo (Uber)
Average rating: *****
(5.00, 2 ratings)
Locations and trips provide insights that can improve business decisions and better serve users, but geospatial data analysis is particularly challenging. It requires efficiency, usability, and scalability in order to meet user needs and business requirements. Join Zhenxiao Luo to learn how Uber uses artificial intelligence to analyze geospatial big data, one of its distinct challenges. Read more.
Add to your personal schedule
14:50–15:30 Friday, 2019-06-21
40分钟议题 (40-minute session)
企业人工智能 (AI in the Enterprise), 实施人工智能 (Implementing AI), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2)
AI pipelines simplify the lifecycle workflow management and enhance reproducibility and collaboration for machine learning and deep learning projects. Cloud native platform solutions offer great portability and scalability. Weiqiang Zhuang and Huaxin Gao show how, by combining strengths, AI pipelines on container platforms can help accelerate AI application development and deployment. Read more.
Add to your personal schedule
14:50–15:30 Friday, 2019-06-21
40分钟议题 (40-minute session)
人工智能对商业及社会的影响 (Impact of AI on Business and Society)
Location: 多功能厅5A+B(Function Room 5A+B)
Hongyu Cui (DataVisor)
AI技术在赋能各个产业的同时,也被网络黑产所利用,使得黑产攻击更加自动化,更加隐蔽,难于检测。 DataVisor在互联网反欺诈领域研究发现,目前黑产的攻击模型呈现以下趋势:攻击方法多样化而变化快,攻击手段趋于模拟正常用户,攻击账号主要来源由大规模注册渐渐转向ATO账号。传统的规则系统和有监督的模型,由于对欺诈案例以及标签数据的强依赖,往往无法及时应对迅速演化的黑产攻击,在反欺诈中一直处于被动防守的状态。DataVisor的无监督算法,通过全局分析,在高维空间聚类,可以在无标签情况下,自动发现大规模关联欺诈团伙。无监督算法在提前预警以及检测快速演变欺诈模式方面体现了显著的优势。 Read more.
Add to your personal schedule
14:50–15:30 Friday, 2019-06-21
40分钟议题 (40-minute session)
与人工智能交互 (Interacting with AI), 实施人工智能 (Implementing AI)
Location: 多功能厅6A+B (Function Room 6A+B)
杨军 (阿里巴巴), 龙国平 (Alibaba)
本次演讲会介绍阿里计算平台PAI团队过去一年多时间里在深度学习编译器领域的技术工作进展----PAI TAO(Tensor Accelerator and Optimizer)。PAI-TAO采用通用编译优化技术,来解决PAI平台所承载的多样性AI workload面临的训练及推理需求的性能优化问题,在部分workload上获得了20%到4X不等的显著加速效果,并且基本作到用户层全透明,在显著提升平台效率性能的同时也有效照顾了用户的使用惯性。目前PAI-TAO已经先后用于支持阿里内部搜索、推荐、图像、文本等多个业务场景的日常训练及推理需求。 Read more.

15:30

15:30–16:20 Friday, 2019-06-21
Location: 报告厅序厅 (Auditorium Foyer)
Afternoon Break (50m)

16:20

16:20–17:00 Friday, 2019-06-21
Location: 紫金大厅B(Grand Hall B)
TBC
Add to your personal schedule
16:20–17:00 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
ju fang (中国人寿研发中心)
分析保险行业人工智能发展情况及现有数据特性,评估机器学习模型构建的主流工具、语言、算法。总结基于机器学习技术,实现一个保险业人工智能场景的全流程——从场景研讨、数据加工提取到模型构建、模型效果评估、模型落地实施。以一个真实的机器学习模型项目为例,介绍整个方法论不同环节中各方人员的参与工作内容和比例,探讨特征稳定性、样本不均衡、参数选择、模型可解释性等环节的难点及尝试方案。为金融或者其他行业的机器学习项目落地提供参考和指导。 Read more.
Add to your personal schedule
16:20–17:00 Friday, 2019-06-21
Le Zhang (Microsoft), Jianxun Lian (Microsoft)
Enterprises benefit from recommendation systems for revenue and customer engagement, but creating such a system is time-consuming. Le Zhang and Jianxun Lian explore the Microsoft/Recommenders repository, which offers solutions to building recommendation systems. It contains classic and state-of-the-art algorithms from Microsoft and enables enterprise success by leveraging Azure's cloud capability. Read more.
Add to your personal schedule
16:20–17:00 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅5A+B(Function Room 5A+B)
李苍柏 (中国地质科学院矿产资源研究所)
Average rating: *....
(1.00, 1 rating)
矿床所在的位置往往伴随着地质、地球物理、地球化学、遥感异常,因此,这些异常所在的位置也往往伴随着矿床的存在。所以,在找矿工作当中,一个重要的过程便是在地、物、化、遥数据中寻找异常,并将其整合,得出该区域成矿的概率,从而推断出靶区所在的位置。但传统方法并未考虑空间中点与点之间的相关关系。而卷积神经网络中的卷积和池化方法,充分考虑了点与点之间的相关关系。但单纯使用卷积神经网络只能进行特征提取,不能圈定异常所在的区域。因此,特将目标检测的相关算法引入其中,从而圈定异常所在的区域。 Read more.
Add to your personal schedule
16:20–17:00 Friday, 2019-06-21
40分钟议题 (40-minute session)
实施人工智能 (Implementing AI)
Location: 多功能厅6A+B (Function Room 6A+B)
Lei Xia (Intel)
Vector neural network instructions (VNNI) is the new Intel instruction set for low-precision AI inference inside the next-generation Xeon platform. Lei Xia offers an overview of the VNNI and Intel software tools, helping you use this new instruction set to accelerate inference with INT8. Read more.