Jonathan Lacotte | DeepAI

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∙ 03/06/2023

Globally Optimal Training of Neural Networks with Threshold Activation Functions

Threshold activation functions are highly preferable in neural networks ...

0 Tolga Ergen, et al. ∙

∙ 07/15/2021

Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update

In second-order optimization, a potential bottleneck can be computing th...

9 Michał Dereziński, et al. ∙

∙ 05/15/2021

Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality

We propose a randomized algorithm with quadratic convergence rate for co...

6 Jonathan Lacotte, et al. ∙

∙ 04/29/2021

Fast Convex Quadratic Optimization Solvers with Adaptive Sketching-based Preconditioners

We consider least-squares problems with quadratic regularization and pro...

7 Jonathan Lacotte, et al. ∙

∙ 12/13/2020

Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds

We propose novel randomized optimization methods for high-dimensional co...

9 Jonathan Lacotte, et al. ∙

∙ 06/10/2020

All Local Minima are Global for Two-Layer ReLU Neural Networks: The Hidden Convex Optimization Landscape

We are interested in two-layer ReLU neural networks from an optimization...

12 Jonathan Lacotte, et al. ∙

∙ 06/10/2020

Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization

We propose a new randomized algorithm for solving L2-regularized least-s...

3 Jonathan Lacotte, et al. ∙

∙ 02/21/2020

Optimal Randomized First-Order Methods for Least-Squares Problems

We provide an exact analysis of a class of randomized algorithms for sol...

0 Jonathan Lacotte, et al. ∙

∙ 02/03/2020

Limiting Spectrum of Randomized Hadamard Transform and Optimal Iterative Sketching Methods

We provide an exact analysis of the limiting spectrum of matrices random...

0 Jonathan Lacotte, et al. ∙

∙ 11/06/2019

Faster Least Squares Optimization

We investigate randomized methods for solving overdetermined linear leas...

0 Jonathan Lacotte, et al. ∙

∙ 06/27/2019

High-Dimensional Optimization in Adaptive Random Subspaces

We propose a new randomized optimization method for high-dimensional pro...

0 Jonathan Lacotte, et al. ∙

∙ 08/13/2018

Risk-Sensitive Generative Adversarial Imitation Learning

We study risk-sensitive imitation learning where the agent's goal is to ...

0 Jonathan Lacotte, et al. ∙

∙ 11/28/2017

Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods

The literature on Inverse Reinforcement Learning (IRL) typically assumes...

0 Sumeet Singh, et al. ∙

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