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02/09/2023
Tree Learning: Optimal Algorithms and Sample Complexity
We study the problem of learning a hierarchical tree representation of d...
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05/27/2022
HOUDINI: Escaping from Moderately Constrained Saddles
We give the first polynomial time algorithms for escaping from high-dime...
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05/21/2021
Escaping Saddle Points with Compressed SGD
Stochastic gradient descent (SGD) is a prevalent optimization technique ...
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12/15/2020
Objective-Based Hierarchical Clustering of Deep Embedding Vectors
We initiate a comprehensive experimental study of objective-based hierar...
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12/15/2019
Bisect and Conquer: Hierarchical Clustering via Max-Uncut Bisection
Hierarchical Clustering is an unsupervised data analysis method which ha...
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10/13/2019
Fast Fourier Sparsity Testing
A function f : F_2^n →R is s-sparse if it has at most s non-zero Fourier...
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10/12/2019
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack
The problem of selecting a small-size representative summary of a large ...
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07/01/2019
Approximate F_2-Sketching of Valuation Functions
We study the problem of constructing a linear sketch of minimum dimensio...
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05/07/2019
Adversarially Robust Submodular Maximization under Knapsack Constraints
We propose the first adversarially robust algorithm for monotone submodu...
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02/10/2019
Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent
Motivated by performance optimization of large-scale graph processing sy...
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12/27/2018
Hierarchical Clustering for Euclidean Data
Recent works on Hierarchical Clustering (HC), a well-studied problem in ...
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09/24/2018
Optimality of Linear Sketching under Modular Updates
We study the relation between streaming algorithms and linear sketching ...
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10/04/2017
