20:53

SysML 2019: Jianyu Wang, Adaptive Communication Strategies in Local-Update SGD

22:28

SysML 19: Assaf Eisenman, Bandana: Using Non-Volatile Memory for Storing Deep Learning Models

24:20

SysML 19: Adam Lerer, Pytorch-BigGraph: A Large Scale Graph Embedding System

18:39

SysML 19: Daniel Smilkov, TensorFlow.js: Machine Learning for the Web and Beyond

16:38

SysML 19: Dan Moldovan, AutoGraph: Imperative-style Coding with Graph-based Performance

20:22

SysML 19: Sven Mika, RLgraph: Modular Computation Graphs for Deep Reinforcement Learning

1:58

SysML 19: Closing Remarks, Ameet Talwalkar

29:52

SysML 19 Keynote: Maya Gupta, How do we make AI fair?

19:29

SysML 19: Akshay Agrawal, TensorFlow Eager: A multi-stage, Python-embedded DSL for machine learning

18:05

SysML 19: Paul Whatmough, FixyNN

21:59

SysML 19: Christopher Canel, Scaling Video Analytics on Constrained Edge Nodes

20:32

SysML 19: Anand Jayarajan, Priority-based Parameter Propagation for Distributed DNN Training

18:32

SysML 19: Demo Previews

18:28

SysML 19: Dibakar Gope, Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications

20:15

SysML 19: Georgios Damaskinos, AggregaThor

20:23

SysML 19: Cedric Renggli, Continuous Integration of Machine Learning Models with ease.ml/ci

18:00

SysML 19: Huizi Mao, CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video

26:11

SysML 19: Jia Zhihao, Beyond Data and Model Parallelism for Deep Neural Networks

20:20

SysML 19: Jian Zhang, YellowFin and the Art of Momentum Tuning

19:20

SysML 19: Jungwook Choi, Accurate and Efficient 2-bit Quantized Neural Networks

16:19

SysML 19: Lei Qi, Discrete Adversarial Attacks and Submodular Optimization

24:12

SysML 19: Martin Zinkevich, Data Validation for Machine Learning

5:32

SysML 19: Matei Zaharia, Opening Remarks

16:47

SysML 19: Maximilian Golub, Full Deep Neural Network Training on a Pruned Weight Budget

23:06

SysML 19: Miguel Mehdi, ParMAC: Distributed Optimisation of Nested Functions

21:34

SysML 19: Minsik Cho, BlueConnect

31:27

SysML 19 Keynote: Ofer Dekel, Compiling AI for the Edge

22:08

SysML 19: Sangkug Lym, Mini-batch Serialization: CNN Training with Inter-layer Data Reuse

22:05

SysML 19: Sayed Hadi Hashemi, TicTac

18:48

SysML 19: Siyuan Ma, Kernel machines that adapt to GPUs for effective large batch training

21:23

SysML 19: Tian Zhao, Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator

20:15

SysML 19: Ting-Wu Chin, AdaScale: Towards Real-time Video Object Detection using Adaptive Scaling

22:30

SysML 19: Wolfgang Grieskamp, Towards Federated Learning at Scale: System Design

22:48

SysML 19: Wonkyung Jung, Restructuring Batch Normalization to Accelerate CNN Training

16:17

SysML 19: Yiren Zhao, To compress or not to compress

20:47

SysML 19: Zhihao Jia, Optimizing DNN Computation with Relaxed Graph Substitutions

9:11

SysML 19: Ameet Talwalkar, Opening Remarks

4:13

SysML 18: Ameet Talwalkar, Opening Remarks

39:51

SysML 18: Jeff Dean, Systems and Machine Learning Symbiosis

11:53

SysML 18: Thibault Sellam, Inspecting the Internal Logic of Recurrent Neural Networks

8:15

SysML 18: Matteo Interlandi, Towards High-Performance Prediction Serving Systems

10:04

SysML 18: Vivienne Sze, Limitations of Energy-Efficient Design Approaches for Deep Neural Networks

37:18

SysML 18: Lise Getoor, Structured ML: Opportunities and Challenges for the SysML Community

38:54

SysML 18: Dawn Song, Security, Privacy, and Democratization

10:30

SysML 18: Ioannis Mitliagkas, YellowFin: Adaptive Optimization for (A)synchronous Systems

36:59

SysML 18: Bill Dally, Hardware for Deep Learning

7:35

SysML 18: Jonathan Binas, Analog electronic deep networks for fast and efficient inference

10:50

SysML 18: Arya Mazumdar, Robust Gradient Descent via Moment Encoding with LDPC Codes

40:27

SysML 18: Michael Jordan, Perspectives and Challenges

10:43

SysML 18: Tianqi Chen, TVM: End-to-End Compilation Stack for Deep Learning