Jerry Chee

21 papers A* 6A 2C 1Journal 10Unranked 2
YearRankTypeTitle / Venue / Authors
2025 — conf
Datasets for Navigating Sensitive Topics in Recommendation Systems.
WWW (Companion Volume)
Amelia Kovacs, Jerry Chee, Sarah Dean
2025 J jnl
Datasets for Navigating Sensitive Topics in Recommendation Systems.
CoRR
Amelia Kovacs, Jerry Chee, Kimia Kazemian, Sarah Dean
2025 A* conf
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory.
COLT
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi
2025 J jnl
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory.
CoRR
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi
2024 A* conf
Harm Mitigation in Recommender Systems under User Preference Dynamics.
KDD
Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis
2024 J jnl
Harm Mitigation in Recommender Systems under User Preference Dynamics.
CoRR
Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis
2024 A* conf
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks.
ICML
Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa
2024 J jnl
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks.
CoRR
Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa
2023 A conf
"Plus/minus the learning rate": Easy and Scalable Statistical Inference with SGD.
AISTATS
Jerry Chee, Hwanwoo Kim, Panos Toulis
2023 A* conf
QuIP: 2-Bit Quantization of Large Language Models With Guarantees.
NeurIPS
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa
2023 J jnl
QuIP: 2-Bit Quantization of Large Language Models With Guarantees.
CoRR
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa
2022 A* conf
How Low Can We Go: Trading Memory for Error in Low-Precision Training.
ICLR
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
2022 A* conf
Model Preserving Compression for Neural Networks.
NeurIPS
Jerry Chee, Megan Flynn, Anil Damle, Christopher De Sa
2022 C conf
Performance optimizations on U-Net speech enhancement models.
MMSP
Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler
2021 J jnl
How Low Can We Go: Trading Memory for Error in Low-Precision Training.
CoRR
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
2021 J jnl
Performance optimizations on deep noise suppression models.
CoRR
Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler
2021 J jnl
Pruning Neural Networks with Interpolative Decompositions.
CoRR
Jerry Chee, Megan Renz, Anil Damle, Chris De Sa
2020 — conf
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum.
IEEE BigData
Jerry Chee, Ping Li
2020 J jnl
Understanding and Detecting Convergence for Stochastic Gradient Descent with Momentum.
CoRR
Jerry Chee, Ping Li
2018 A conf
Convergence diagnostics for stochastic gradient descent with constant learning rate.
AISTATS
Jerry Chee, Panos Toulis
2017 J jnl
Convergence diagnostics for stochastic gradient descent with constant step size.
CoRR
Jerry Chee, Panos Toulis