970 citations · 3k across the 88 of their papers we have counts for
11 papers · 1 filter
Structured Optimal Transport
David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka
Optimal Transport has recently gained interest in machine learning for applications ranging from domain adaptation, sentence similarities to deep learning. Yet, its ability to capt…
Graph-Sparse Logistic Regression
Alexander LeNail, Ludwig Schmidt, Johnathan Li +4
We introduce Graph-Sparse Logistic Regression, a new algorithm for classification for the case in which the support should be sparse but connected on a graph. We val- idate this al…
Distributional Adversarial Networks
Chengtao Li, David Alvarez-Melis, Keyulu Xu +2
We propose a framework for adversarial training that relies on a sample rather than a single sample point as the fundamental unit of discrimination. Inspired by discrepancy measure…
Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly
Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
The need for real time analysis of rapidly producing data streams (e.g., video and image streams) motivated the design of streaming algorithms that can efficiently extract and summ…
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang, Clement Gehring, Pushmeet Kohli +1
Bayesian optimization (BO) has become an effective approach for black-box function optimization problems when function evaluations are expensive and the optimum can be achieved wit…
Parallel Streaming Wasserstein Barycenters
Matthew Staib, Sebastian Claici, Justin Solomon +1
Efficiently aggregating data from different sources is a challenging problem, particularly when samples from each source are distributed differently. These differences can be inher…
Sensor Array Design Through Submodular Optimization
Gal Shulkind, Stefanie Jegelka, Gregory W. Wornell
We consider the problem of far-field sensing by means of a sensor array. Traditional array geometry design techniques are agnostic to prior information about the far-field scene. H…
Polynomial Time Algorithms for Dual Volume Sampling
Chengtao Li, Stefanie Jegelka, Suvrit Sra
We study dual volume sampling, a method for selecting k columns from an n x m short and wide matrix (n <= k <= m) such that the probability of selection is proportional to the volu…
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang, Chengtao Li, Stefanie Jegelka +1
Optimization of high-dimensional black-box functions is an extremely challenging problem. While Bayesian optimization has emerged as a popular approach for optimizing black-box fun…
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang, Stefanie Jegelka
Entropy Search (ES) and Predictive Entropy Search (PES) are popular and empirically successful Bayesian Optimization techniques. Both rely on a compelling information-theoretic mot…
Robust Budget Allocation via Continuous Submodular Functions
Matthew Staib, Stefanie Jegelka
The optimal allocation of resources for maximizing influence, spread of information or coverage, has gained attention in the past years, in particular in machine learning and data…