Sahand Negahban
14 papers · 2008–2021 · 5 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (14) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (5)
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(13)
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Cross-Pollinator
(15)
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Renaissance Researcher
(5)
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Keyword Trendsetter Combo
(5)
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Keyword Champion
(2)
π±
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Century Club
(14)
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(5)
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Keyword Collector
(98)
Conferences
NIPS (7)
ICML (3)
JMLR (2)
AISTATS (1)
COLT (1)
Top co-authors
Keywords
restricted strong convexity
(4)
convergence rate
(3)
convex optimization
(2)
greedy algorithm
(2)
matrix completion
(2)
sparse regression
(2)
high-dimensional statistics
(2)
sparse optimization
(2)
matrix estimation
(2)
feature selection
(2)
gradient descent
(2)
preference learning
(2)
global convergence
(1)
supervised learning
(1)
sparse recovery
(1)
collaborative filtering
(1)
learning theory
(1)
statistical learning
(1)
distributed optimization
(1)
sparse learning
(1)
Papers
Distributed Machine Learning with Sparse Heterogeneous Data
NIPS 2021
Feature Selection using Stochastic Gates
ICML 2020
Tree-projected gradient descent for estimating gradient-sparse parameters on graphs
COLT 2020
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
ICML 2019
Learning from Comparisons and Choices
JMLR 2018
Scalable Greedy Feature Selection via Weak Submodularity
AISTATS 2017
Minimax Estimation of Bandable Precision Matrices
NIPS 2017
On Approximation Guarantees for Greedy Low Rank Optimization
ICML 2017
Iterative ranking from pair-wise comparisons
NIPS 2012
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions
NIPS 2012
Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise
JMLR 2012
Fast global convergence rates of gradient methods for high-dimensional statistical recovery
NIPS 2010
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
NIPS 2009
Phase transitions for high-dimensional joint support recovery
NIPS 2008