Stanford MLSys Seminars
Stanford seminar on the frontier of machine learning and systems. Live every Thursday, 1:15-3 pm PT.
How Netflix does MLSys feat. Savin Goyal | Stanford MLSys Seminar Episode 17
Improving Transfer and Robustness of Supervised Contrastive Learning - Dan Fu | Stanford MLSys #62
MLSys Singapore
MLSys Seminar @SG is a special interest group for Machine Learning System researchers and engineers in Singapore. We meet ...
What can Data-Centric AI Learn from Data and ML Engineering? - Alkis Polyzotis | Stanford MLSys #65
Declarative Machine Learning with Ludwig feat. Piero Molino | Stanford MLSys Seminar Episode 13
What do Machines Know? feat. Fabio Petroni | Stanford MLSys Seminar Episode 16
Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu | Stanford MLSys #46
Disrupting Distributed ML feat. Guanhua Wang | Stanford MLSys Seminar Episode 25
Distributed ML with H2O feat. Erin LeDell | Stanford MLSys Seminar Episode 23
Machine Learning Everywhere feat. Pete Warden | Stanford MLSys Seminar Episode 31
ML Frameworks for Chatbots feat. Chris Kedzie | Stanford MLSys Seminar Episode 34
Bridging Models and Data feat. Willem Pienaar | Stanford MLSys Seminar Episode 32
Deep Recommender Systems at Facebook feat. Carole-Jean Wu | Stanford MLSys Seminar Episode 24
MLSys'24 Best Paper - AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Automating Architecture Transfer feat. Ameet Talwalkar | Stanford MLSys Seminar Episode 19
“Boring” Problems in Distributed ML feat. Richard Liaw | Stanford MLSys Seminar Episode 28
![[MLSys 2022] BNS-GCN](/vi/kzI0ksASFQY/mqdefault.jpg)
MLSys'2021: RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads (Full Talk)
What is the Hardware Lottery? feat. Sara Hooker | Stanford MLSys Seminar Episode 15
![[MLSys'21][Poster] Fluid: Resource-aware Hyperparameter Tuning Engine](/vi/yaBxEUxRXZI/mqdefault.jpg)
Distributed Neural Search feat. Rutuja Surve | Stanford MLSys Seminar Episode 21
How ML Optimizes Data Systems feat. Tim Kraska | Stanford MLSys Seminar Episode 26
How Facebook/Meta Design Sustainable Datacenters with AI - Bilge Acun | Stanford MLSys #52
![[MLSys'21][Oral] Fluid: Resource-aware Hyperparameter Tuning Engine](/vi/LZQE90whvfY/mqdefault.jpg)
Robustness/Interpretability in Vision & Language Models - Arjun Akula | Stanford MLSys #63
Resource-Efficient Deep Learning Execution - Deepak Narayanan | Stanford MLSys #50
Poisoning Web-Scale Training Datasets - Nicholas Carlini | Stanford MLSys #75
Scalable Binary Analysis for Security feat. Suman Jana | Stanford MLSys Seminar Episode 36
Causal AI for Systems feat. Pooyan Jamshidi | Stanford MLSys Seminar Episode 38
Software 2.0 for Data Quality feat. Theodoros Rekatsinas | Stanford MLSys Seminar Episode 18
The Missing Link in ML Infrastructure feat. Josh Tobin | Stanford MLSys Seminar Episode 11
Large Language Models for Program Optimization - Osbert Bastani | Stanford MLSys #91
MLSys'2021: RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads (Lightning)
Video Analysis in Hours, Not Weeks feat. Kayvon Fatahalian | Stanford MLSys Seminar Episode 8
![Scaling Polyhedral Neural Network Verification on GPUs [MLSys'21]](/vi/rM95uwgFFVw/mqdefault.jpg)
Comet CEO Gideon Mendels on why industry is behind academia in machine learning
Alpa: Automated Model-Parallel Deep Learning - Zhuohan Li | Stanford MLSys #59
How NVIDIA Supports Recommender Systems feat. Even Oldridge | Stanford MLSys Seminar Episode 27
Distributed ML for Federated Learning feat. Chaoyang He | Stanford MLSys Seminar Episode 37
Reshaping ML with Compilers feat. Jason Knight | Stanford MLSys Seminar Episode 22
Debugging ML in Production feat. Shreya Shankar | Stanford MLSys Seminar Episode 12
Learning from MASSIVE data feat UCLA Prof Baharan Mirzasoleiman | Stanford MLSys #45
ML Ops at Reasonable Scale feat. Jacopo Tagliabue | Stanford MLSys Seminar Episode 35
USC Information Sciences Institute
Distributed ML System for Large-scale Models: Dynamic Distributed Training
MIT Prof. Song Han on Reducing AI's Carbon Footprint | Stanford MLSys Seminar Episode 9
Comet CEO Gideon Mendels on what Tesla has to overcome for full self-driving
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