Zachary Chase Lipton

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 28

Top Venues

CoRR

ICLR

ICML

AISTATS

University of California, San Diego, USA (PHD)

Education History

University of California, San Diego, USA

PHD

Publications

Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan
T-MARS: Improving Visual Representations by Circumventing Text Feature Learning. ICLR (2024)
Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Chase Lipton
Post-Hoc Reversal: Are We Selecting Models Prematurely? CoRR (2024)
Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola
Time-Varying Propensity Score to Bridge the Gap between the Past and Present. ICLR (2024)
Shantanu Gupta, David Childers, Zachary Chase Lipton
Local Causal Discovery for Estimating Causal Effects. CLeaR (2023)
Zachary Chase Lipton
Reliable deep learning in dynamic environments. Medical Imaging: Computer-Aided Diagnosis (2023)
Pratyush Maini, Michael Curtis Mozer, Hanie Sedghi, Zachary Chase Lipton, J. Zico Kolter, Chiyuan Zhang
Can Neural Network Memorization Be Localized? ICML (2023)
Zachary Novack, Julian J. McAuley, Zachary Chase Lipton, Saurabh Garg
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. ICML (2023)
Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton
RLSbench: Domain Adaptation Under Relaxed Label Shift. ICML (2023)
Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Andrej Risteski
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective. ICML (2023)
Saurabh Garg, Amrith Setlur, Zachary Chase Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift. CoRR (2023)
Yifan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric P. Xing
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation. Trans. Mach. Learn. Res. 2023 (2023)
Zachary Novack, Simran Kaur, Tanya Marwah, Saurabh Garg, Zachary Chase Lipton
Disentangling the Mechanisms Behind Implicit Regularization in SGD. ICLR (2023)
Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary Chase Lipton, Yu-Xiang Wang
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms. CoRR (2023)
Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi
Leveraging unlabeled data to predict out-of-distribution performance. ICLR (2022)
Simran Kaur, Jeremy Cohen, Zachary Chase Lipton
On the Maximum Hessian Eigenvalue and Generalization. ICBINB (2022)
Audrey Huang, Liu Leqi, Zachary Chase Lipton, Kamyar Azizzadenesheli
Off-Policy Risk Assessment in Markov Decision Processes. CoRR (2022)
Divyansh Kaushik, Amrith Setlur, Eduard H. Hovy, Zachary Chase Lipton
Explaining the Efficacy of Counterfactually Augmented Data. ICLR (2021)
Kyra Gan, Andrew A. Li, Zachary Chase Lipton, Sridhar R. Tayur
Causal Inference with Selectively Deconfounded Data. AISTATS (2021)
Divyansh Kaushik, Eduard H. Hovy, Zachary Chase Lipton
Learning The Difference That Makes A Difference With Counterfactually-Augmented Data. ICLR (2020)
Mohammad Taha Bahadori, Zachary Chase Lipton
Temporal-Clustering Invariance in Irregular Healthcare Time Series. CoRR (2019)
Jonathon Byrd, Zachary Chase Lipton
What is the Effect of Importance Weighting in Deep Learning? ICML (2019)
Fan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen
Game Design for Eliciting Distinguishable Behavior. NeurIPS (2019)
Tommaso Furlanello, Zachary Chase Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar
Born-Again Neural Networks. ICML (2018)
Yanyao Shen, Hyokun Yun, Zachary Chase Lipton, Yakov Kronrod, Animashree Anandkumar
Deep Active Learning for Named Entity Recognition. Rep4NLP@ACL (2017)
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series. CoRR (2016)
Zachary Chase Lipton
The Mythos of Model Interpretability. CoRR (2016)
Zachary Chase Lipton
Stuck in a What? Adventures in Weight Space. CoRR (2016)
Zachary Chase Lipton, David C. Kale, Charles Elkan, Randall C. Wetzel
Learning to Diagnose with LSTM Recurrent Neural Networks. ICLR (Poster) (2016)
Zachary Chase Lipton, Charles Elkan
Efficient Elastic Net Regularization for Sparse Linear Models. CoRR (2015)
Zachary Chase Lipton, Sharad Vikram, Julian J. McAuley
Capturing Meaning in Product Reviews with Character-Level Generative Text Models. CoRR (2015)
Zachary Chase Lipton
A Critical Review of Recurrent Neural Networks for Sequence Learning. CoRR (2015)
Zachary Chase Lipton, David C. Kale, Randall C. Wetzel
Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks. CoRR (2015)
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
F1-Optimal Thresholding in the Multi-Label Setting. CoRR (2014)
Zhanglong Ji, Zachary Chase Lipton, Charles Elkan
Differential Privacy and Machine Learning: a Survey and Review. CoRR (2014)
Zachary Chase Lipton, Charles Elkan, Balakrishnan Narayanaswamy
Optimal Thresholding of Classifiers to Maximize F1 Measure. ECML/PKDD (2) (2014)

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Publication Activity (10 Years)

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Zachary Chase Lipton