Sequence-level large language model training with noise contrastive preference optimization
Link to Work in progress
Text descriptions are compressive and invariant representations for visual learning
with Anna Bair, Zico Kolter
https://arxiv.org/abs/2307.04317
Monotone deep Boltzmann machines
with Ezra Winston, Zico Kolter
TMLR2023
On the neural tangent kernel of equilibrium models
with Zico Kolter
https://arxiv.org/pdf/2310.14062.pdf
Provable adaptation across multiway domains via representation learning
with Shaobo Han, and Simon S. Du
ICLR2021
Non-psd matrix sketching with applications to regression and optimization
with Fred Roosta, and David P. Woodruff
UAI2021
Learning-augmented k-means clustering
with Jon Ergun, Sandeep Silwal, David P. Woodruff, and Samson Zhou
ICLR 2021
Dimensionality reduction for the sum-of-distances metric
with Praneeth Kacham, and David Woodruff
ICML 2021
Does data augmentation lead to positive margin?
with Shashank Rajput, Zachary B. Charles, Po-Ling Loh, and Dimitris S. Papailiopoulos
ICML 2019
Online learning with graph-structured feedback against adaptive adversaries
with Po-Ling Loh
ISIT 2018
Joint reasoning for temporal and causal relations
with Qiang Ning, and Dan Roth
ACL 2018
A structured learning approach to temporal relation extraction
with Qiang Ning, and Dan Roth
EMNLP 2017

Zhili Feng