research
∙
06/30/2023
An Oblivious Stochastic Composite Optimization Algorithm for Eigenvalue Optimization Problems
In this work, we revisit the problem of solving large-scale semidefinite...
share
research
∙
04/22/2023
Vision Transformers, a new approach for high-resolution and large-scale mapping of canopy heights
Accurate and timely monitoring of forest canopy heights is critical for ...
research
∙
11/03/2022
Optimal Algorithms for Stochastic Complementary Composite Minimization
Inspired by regularization techniques in statistics and machine learning...
research
∙
03/10/2021
Linear Bandits on Uniformly Convex Sets
Linear bandit algorithms yield 𝒪̃(n√(T)) pseudo-regret bounds on compact...
research
∙
02/09/2021
Local and Global Uniform Convexity Conditions
We review various characterizations of uniform convexity and smoothness ...
research
∙
01/23/2021
Acceleration Methods
This monograph covers some recent advances on a range of acceleration te...
research
∙
11/05/2020
A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs
We develop a Bregman proximal gradient method for structure learning on ...
research
∙
10/29/2020
Convergence of Constrained Anderson Acceleration
We prove non asymptotic linear convergence rates for the constrained And...
research
∙
10/06/2020
Averaging Atmospheric Gas Concentration Data using Wasserstein Barycenters
Hyperspectral satellite images report greenhouse gas concentrations worl...
research
∙
06/22/2020
An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention
We introduce a kernel for sets of features based on an optimal transport...
research
∙
06/15/2020
FANOK: Knockoffs in Linear Time
We describe a series of algorithms that efficiently implement Gaussian m...
research
∙
02/06/2020
Global Convergence of Frank Wolfe on One Hidden Layer Networks
We derive global convergence bounds for the Frank Wolfe algorithm when t...
research
∙
02/03/2020
Complexity Guarantees for Polyak Steps with Momentum
In smooth strongly convex optimization, or in the presence of Hölderian ...
research
∙
12/05/2019
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Function
We design simple screening tests to automatically discard data samples i...
research
∙
11/19/2019
Optimal Complexity and Certification of Bregman First-Order Methods
We provide a lower bound showing that the O(1/k) convergence rate of the...
research
∙
06/06/2019
Ranking and synchronization from pairwise measurements via SVD
Given a measurement graph G= (V,E) and an unknown signal r ∈R^n, we inve...
research
∙
05/26/2019
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport
The problem of estimating Wasserstein distances in high-dimensional spac...
research
∙
05/23/2019
Naive Feature Selection: Sparsity in Naive Bayes
Due to its linear complexity, naive Bayes classification remains an attr...
research
∙
01/24/2019
Overcomplete Independent Component Analysis via SDP
We present a novel algorithm for overcomplete independent components ana...
research
∙
07/18/2018
Reconstructing Latent Orderings by Spectral Clustering
Spectral clustering uses a graph Laplacian spectral embedding to enhance...
research
∙
06/01/2018
Nonlinear Acceleration of CNNs
The Regularized Nonlinear Acceleration (RNA) algorithm is an acceleratio...
research
∙
05/24/2018
Nonlinear Acceleration of Deep Neural Networks
Regularized nonlinear acceleration (RNA) is a generic extrapolation sche...
research
∙
03/20/2018
Frank-Wolfe with Subsampling Oracle
We analyze two novel randomized variants of the Frank-Wolfe (FW) or cond...
research
∙
06/20/2014