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
Deep Recommender Systems at Facebook feat. Carole-Jean Wu | Stanford MLSys Seminar Episode 24
MLSys Singapore
MLSys Seminar @SG is a special interest group for Machine Learning System researchers and engineers in Singapore. We meet ...
Improving Transfer and Robustness of Supervised Contrastive Learning - Dan Fu | Stanford MLSys #62
Declarative Machine Learning with Ludwig feat. Piero Molino | Stanford MLSys Seminar Episode 13
Jeff Dean (Google Research & Deep Mind): Advances in ML for Systems and Systems for ML | MLSys 2024
Automating Architecture Transfer feat. Ameet Talwalkar | Stanford MLSys Seminar Episode 19
Monarch Mixer: Making Foundation Models More Efficient - Dan Fu | Stanford MLSys #86
MLSys'24 Best Paper - AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
How ML Optimizes Data Systems feat. Tim Kraska | Stanford MLSys Seminar Episode 26
What is the Hardware Lottery? feat. Sara Hooker | Stanford MLSys Seminar Episode 15
MLSys'2021: RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads (Full Talk)
Efficiently Modeling Long Sequences with Structured State Spaces - Albert Gu | Stanford MLSys #46
“Boring” Problems in Distributed ML feat. Richard Liaw | Stanford MLSys Seminar Episode 28
What can Data-Centric AI Learn from Data and ML Engineering? - Alkis Polyzotis | Stanford MLSys #65
![[MLSys'21][Oral] Fluid: Resource-aware Hyperparameter Tuning Engine](/vi/LZQE90whvfY/mqdefault.jpg)
![[MLSys'21][Poster] Fluid: Resource-aware Hyperparameter Tuning Engine](/vi/yaBxEUxRXZI/mqdefault.jpg)
Disrupting Distributed ML feat. Guanhua Wang | Stanford MLSys Seminar Episode 25
Machine Learning Everywhere feat. Pete Warden | Stanford MLSys Seminar Episode 31
MLSys'2021: RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads (Lightning)
What do Machines Know? feat. Fabio Petroni | Stanford MLSys Seminar Episode 16
Bridging Models and Data feat. Willem Pienaar | Stanford MLSys Seminar Episode 32
Automating Architecture Transfer feat. Ameet Talwalkar | Stanford MLSys Seminar Episode 19
Comet CEO Gideon Mendels on why industry is behind academia in machine learning
ML Frameworks for Chatbots feat. Chris Kedzie | Stanford MLSys Seminar Episode 34
Causal AI for Systems feat. Pooyan Jamshidi | Stanford MLSys Seminar Episode 38
Resource-Efficient Deep Learning Execution - Deepak Narayanan | Stanford MLSys #50
The Missing Link in ML Infrastructure feat. Josh Tobin | Stanford MLSys Seminar Episode 11
Distributed Neural Search feat. Rutuja Surve | Stanford MLSys Seminar Episode 21
What can Data-Centric AI Learn from Data and ML Engineering? - Alkis Polyzotis | Stanford MLSys #65
Building ML Models like Open-Source Software - Colin Raffel | Stanford MLSys #72
Robustness/Interpretability in Vision & Language Models - Arjun Akula | Stanford MLSys #63
![[MLSys 2022] BNS-GCN](/vi/kzI0ksASFQY/mqdefault.jpg)
How Uber Predicts Arrival Times - Xinyu Hu and Olcay Cirit | Stanford MLSys #64
Scalable Binary Analysis for Security feat. Suman Jana | Stanford MLSys Seminar Episode 36
![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
Software 2.0 for Data Quality feat. Theodoros Rekatsinas | Stanford MLSys Seminar Episode 18
Distributed ML for Federated Learning feat. Chaoyang He | Stanford MLSys Seminar Episode 37
Poisoning Web-Scale Training Datasets - Nicholas Carlini | Stanford MLSys #75
Debugging ML in Production feat. Shreya Shankar | Stanford MLSys Seminar Episode 12
MIT Prof. Song Han on Reducing AI's Carbon Footprint | Stanford MLSys Seminar Episode 9
