Research Papers

The following is chronological listing of published and pre-printed academic publications.

Born Again Networks
Tommaso Furlanello, Zachary C Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar
ICML 2018

Detecting and Correcting for Label Shift with Black Box Predictors
Zachary C. Lipton, Yu-Xiang Wang, Alex Smola
ICML 2018

Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
Chris Donahue, Zachary C. Lipton, Akshay Balsubramani, Julian McAuley
ICLR 2018

Stochastic Activation Pruning for Robust Adversarial Defense
Guneet Dhillon Singh, Kamyar Azizzadenesheli, Jeremy Bernstein, Aran Khanna, Zachary C. Lipton, Anima Anandkumar
ICLR 2018

Learning from Noisy Singly-Labeled data
Ashish Khetan Kumar, Zachary C. Lipton, Anima Anandkumar
ICLR 2018

Deep Active Learning for Named Entity Recognition
Yanyao Shen, Hyokun Yun, Zachary C. Lipton, Anima Anandkumar
ICLR 2018

Does Mitigating ML's Disparate Impact Require Disparate Treatment?
Zachary C. Lipton, Alexandra Chouldechova, Julian McAuley
arXiv 2017

Born Again Networks
Tommaso Furlanello, Zachary C Lipton, Laurent Itti, Anima Anandkumar
NIPS Workshop on Metalearning

Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals
John Alberg and Zachary C. Lipton
NIPS Time Series Workshop 2017

The Doctor Just Won’t Accept That!
Zachary C. Lipton
NIPS Symposium on Interpretable ML 2017

Tensor Regression Networks
Jean Kossaifi, Zachary C. Lipton, Aran Khanna, Tommaso Furlanello, Anima Anandkumar
arXiv 2017

Estimating reactions and recommending products with generative models of reviews
Jianmo Ni, Zachary C. Lipton, Sharad Vikram, Julian McAuley
IJCNLP 2017

Tensor Contraction Layers for Parsimonious Deep Nets
Jean Kossaifi, Aran Khanna, Zachary C. Lipton, Tommasso Furlanello, Anima Anandkumar
Workshop on Tensor Methods in Computer Vision - CVPR

Dance Dance Convolution
Chris Donahue, Zachary C Lipton, Julian McAuley
ICML 2017

Precise Recovery of Latent Vectors for Generative Adversarial Networks
Zachary C. Lipton, Subarna Tripathi
ICLR Workshop 2017 [PDF]

Predicting Surgery Duration with Neural Heteroscedastic Regression
Nathan Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C Lipton
Machine Learning for Healthcare (MLHC) 2017 [PDF]

Dance Dance Convolution (workshop version)
Chris Donahue, Zachary C Lipton, Julian McAuley
ICLR Workshop 2017

Combating Deep Reinforcement Learning's Sisyphean Curse with Intrinsic Fear
Zachary C. Lipton, Jianfeng Gao, Lihong Li, Jianshu Chen, Li Deng
arXiv 2016 [PDF]

Efficient Exploration for Dialogue Policy Learning with BBQ Networks & Replay Buffer Spiking
Zachary C. Lipton, Jianfeng Gao, Lihong Li, Xiujun Li , Faisal Ahmed, Li Deng
NIPS Workshop on Deep Reinforcement Learning (DRL 2016) [PDF]

Context Matters: Refining Object Detection in Video with Recurrent Neural Networks
Subarna Tripathi, Zachary C. Lipton, Serge Belongie, Truong Nguyen
British Machine Vision Conference (BMVC 2016) [PDF]

Modeling Missing Data in Clinical Time Series with RNNs
Zachary C. Lipton, David C. Kale, Randall Wetzel
Machine Learning for Healthcare (MLHC 2016) / Journal of Machine Learning Research [PDF]

The Mythos of Model Interpretability
Zachary C. Lipton
ICML 2016 Workshop on Human Interpretability in Machine Learning (WHI 2016) [PDF]

Learning to Diagnose with LSTM Recurrent Neural Networks
Zachary C. Lipton, David C. Kale, Charles Elkan, Randall Wetzell
International Conference on Learning Representations (ICLR 2016) [PDF]

Playing the Imitation Game with Deep Learning
Zachary C. Lipton, Charles Elkan
IEEE Spectrum - February, 2016 [PDF]

Generative Concatenative Nets Jointly Learn to Write and Classify Reviews
Zachary C. Lipton, Sharad Vikram, Julian McAuley
(arXiv 2015) [PDF]

Phenotyping of Clinical Time Series with LSTM Recurrent Neural Networks
Zachary C. Lipton, David C. Kale, Randall C. Wetzell
NIPS 2015 Workshop on Machine Learning in Healthcare [PDF]

A Critical Review of Recurrent Neural Networks for Sequence Learning
Zachary C. Lipton
(arXiv 2015) [PDF]

Efficient Elastic Net Regularization for Sparse Linear Models
Zachary C. Lipton and Charles Elkan
(arXiv 2015) [PDF]

Differential Privacy and Machine Learning: A Survey and Review
Zhanglong Ji, Zachary C. Lipton, Charles Elkan
(arXiv 2014) [PDF]

Optimal Thresholding of Classifiers to Maximize F1 Measure
Zachary C. Lipton, Charles Elkan, Balakrishnan Narayaswamy
Machine Learning and Knowledge Discovery in Databases. Springer Berlin Heidelberg, 2014. 225-239. (ECML 2014) [PDF]

Estimation of Saxophone Control Parameters by Convex Optimization
Cheng-I Wang, Tamara Smyth, Zachary C. Lipton
Conference for Interdisciplinary Musicology (CIM 2014) [PDF]

zlipton@cs.ucsd.edu