Publications

Robust learning with the Hilbert-Schmidt independence criterion

D Greenfeld, U Shalit


Off-Policy Evaluation in Partially Observable Environments

G Tennenholtz, S Mannor, U Shalit

2019


Building Causal Graphs from Medical Literature and Electronic Medical Records

G Nordon, G Koren, V Shalev, B Kimelfeld, U Shalit, K Radinsky

In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019


Harmonizing Fully Optimal Designs with Classic Randomization in Fixed Trial Experiments

A Kapelner, AM Krieger, U Shalit, D Azriel

2018


Learning Weighted Representations for Generalization Across Designs

FD Johansson, N Kallus, U Shalit, D Sontag

2018


Removing Hidden Confounding by Experimental Grounding

N Kallus, AM Puli, U Shalit

In Proceedings of the 32nd International Conference on Neural Information Processing Systems, of NeurIPS’18, 2018


Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition

V Dorie, J Hill, U Shalit, M Scott, D Cervone

2018


Causal effect inference with deep latent-variable models

C Louizos, U Shalit, JM Mooij, D Sontag, R Zemel, M Welling

In Proceedings of the 31st International Conference on Neural Information Processing Systems, of NeurIPS’17, 2017


Structured Inference Networks for Nonlinear State Space Models

RG Krishnan, U Shalit, D Sontag

In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017


Estimating individual treatment effect: generalization bounds and algorithms

U Shalit, F Johansson, D Sontag

In Proceedings of the 34th International Conference on Machine Learning (ICML), 2017


Learning representations for counterfactual inference

F Johansson, U Shalit, D Sontag

In Proceedings of The 33rd International Conference on Machine Learning (ICML), 2016


Deep Kalman Filters

RG Krishnan, U Shalit, D Sontag

2015


Learning Sparse Metrics, One Feature at a Time

Y Atzmon, U Shalit, G Chechik

Journal of Machine Learning Research, 2015


Coordinate-descent for learning orthogonal matrices through Givens rotations

U Shalit, G Chechik

In International Conference on Machine Learning (ICML), 2014


FuncISH: learning a functional representation of neural ISH images

N Liscovitch, U Shalit, G Chechik

Bioinformatics, 2013


Modeling Musical Influence with Topic Models

U Shalit, D Weinshall, G Chechik

In Proceedings of the 30th International Conference on Machine Learning (ICML), 2013


Descending Systems Translate Transient Cortical Commands into a Sustained Muscle Activation Signal

U Shalit, N Zinger, M Joshua, Y Prut

Cerebral Cortex, 2012


Online Learning in the Embedded Manifold of Low-rank Matrices

U Shalit, D Weinshall, G Chechik

Journal of Machine Learning Research (JMLR), 2012


Large scale online learning of image similarity through ranking

G Chechik, V Sharma, U Shalit, S Bengio

Journal of Machine Learning Research (JMLR), 2010


Online learning in the manifold of low-rank matrices

U Shalit, D Weinshall, G Chechik

In Advances in Neural Information Processing Systems, 2010


An online algorithm for large scale image similarity learning

G Chechik, V Sharma, U Shalit, S Bengio

In Advances in Neural Information Processing Systems, 2009


Computation in spinal circuitry: Lessons from behaving primates

R Harel, I Asher, O Cohen, Z Israel, U Shalit, Y Yanai, N Zinger, Y Prut

Behavioural Brain Research, 2008


Using topic modeling to detect and quantify semantic change

H Dubossarsky, U Shalit, E Grossman, D Weinshall

New Developments in the Quantitative Study of Languages