Sahand Negahban

Publication Activity (10 Years)

Years Active: 2012-2021
Publications (10 Years): 17

Top Topics

Machine Learning

Supervised Feature Selection

Robust Optimization

Top Venues

Nursing Informatics

Publications

Qinghao Liang, Sahand Negahban, Joseph Chang, Harrison H. Zhou, Dustin Scheinost
Connectome-Based Predictive Modelling With Missing Connectivity Data Using Robust Matrix Completion. ISBI (2021)
Dominic Richards, Sahand Negahban, Patrick Rebeschini
Distributed Machine Learning with Sparse Heterogeneous Data. NeurIPS (2021)
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
Feature Selection using Stochastic Gates. ICML (2020)
Sheng Xu, Zhou Fan, Sahand Negahban
Tree-projected gradient descent for estimating gradient-sparse parameters on graphs. COLT (2020)
Sheng Xu, Zhou Fan, Sahand Negahban
Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs. CoRR (2020)
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand Negahban
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback. ICML (2019)
Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu
Learning from Comparisons and Choices. J. Mach. Learn. Res. 19 (2018)
Hamid Dadkhahi, Sahand Negahban
Alternating Linear Bandits for Online Matrix-Factorization Recommendation. CoRR (2018)
Uri Shaham, Yutaro Yamada, Sahand Negahban
Understanding adversarial training: Increasing local stability of supervised models through robust optimization. Neurocomputing 307 (2018)
Satish M. Mahajan, Amey S. Mahajan, Robert King, Sahand Negahban
Predicting Risk of 30-Day Readmissions Using Two Emerging Machine Learning Methods. Nursing Informatics (2018)
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
Deep supervised feature selection using Stochastic Gates. CoRR (2018)
Satish M. Mahajan, Amey S. Mahajan, Sahand Negahban
Regional Differences in Predicting Risk of 30-Day Readmissions for Heart Failure. Nursing Informatics (2018)
Addison Hu, Sahand Negahban
Minimax Estimation of Bandable Precision Matrices. NIPS (2017)
Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu
Learning from Comparisons and Choices. CoRR (2017)
Sahand Negahban, Sewoong Oh, Devavrat Shah
Rank Centrality: Ranking from Pairwise Comparisons. Oper. Res. 65 (1) (2017)
Bobak Mortazavi, Nihar Desai, Jing Zhang, Andreas Coppi, Fred Warner, Harlan M. Krumholz, Sahand Negahban
Prediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures. IEEE J. Biomed. Health Informatics 21 (6) (2017)
Uri Shaham, Yutaro Yamada, Sahand Negahban
Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization. CoRR (2015)
Sahand Negahban, Sewoong Oh, Devavrat Shah
Iterative ranking from pair-wise comparisons. NIPS (2012)
Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
Scaling multiple-source entity resolution using statistically efficient transfer learning. CIKM (2012)
Sahand Negahban, Sewoong Oh, Devavrat Shah
Iterative Ranking from Pair-wise Comparisons CoRR (2012)
Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning CoRR (2012)
Sahand Negahban, Devavrat Shah
Learning sparse Boolean polynomials. Allerton Conference (2012)