Jerry Chee

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Stochastic Gradient Descent

Recommender Systems

Noise Suppression

Top Venues

Publications

Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis
Harm Mitigation in Recommender Systems under User Preference Dynamics. KDD (2024)
Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis
Harm Mitigation in Recommender Systems under User Preference Dynamics. CoRR (2024)
Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks. CoRR (2024)
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa
QuIP: 2-Bit Quantization of Large Language Models With Guarantees. CoRR (2023)
Jerry Chee, Hwanwoo Kim, Panos Toulis
"Plus/minus the learning rate": Easy and Scalable Statistical Inference with SGD. AISTATS (2023)
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa
QuIP: 2-Bit Quantization of Large Language Models With Guarantees. NeurIPS (2023)
Jerry Chee, Megan Flynn, Anil Damle, Christopher De Sa
Model Preserving Compression for Neural Networks. NeurIPS (2022)
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
How Low Can We Go: Trading Memory for Error in Low-Precision Training. ICLR (2022)
Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler
Performance optimizations on U-Net speech enhancement models. MMSP (2022)
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
How Low Can We Go: Trading Memory for Error in Low-Precision Training. CoRR (2021)
Jerry Chee, Megan Renz, Anil Damle, Chris De Sa
Pruning Neural Networks with Interpolative Decompositions. CoRR (2021)
Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler
Performance optimizations on deep noise suppression models. CoRR (2021)
Jerry Chee, Ping Li
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum. IEEE BigData (2020)
Jerry Chee, Ping Li
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum. CoRR (2020)
Jerry Chee, Panos Toulis
Convergence diagnostics for stochastic gradient descent with constant learning rate. AISTATS (2018)
Jerry Chee, Panos Toulis
Convergence diagnostics for stochastic gradient descent with constant step size. CoRR (2017)