Search Results for author: Horia Mania

Found 15 papers, 1 papers with code

Time varying regression with hidden linear dynamics

no code implementations29 Dec 2021 Ali Jadbabaie, Horia Mania, Devavrat Shah, Suvrit Sra

We revisit a model for time-varying linear regression that assumes the unknown parameters evolve according to a linear dynamical system.

Why do classifier accuracies show linear trends under distribution shift?

no code implementations31 Dec 2020 Horia Mania, Suvrit Sra

Recent studies of generalization in deep learning have observed a puzzling trend: accuracies of models on one data distribution are approximately linear functions of the accuracies on another distribution.

Bandit Learning in Decentralized Matching Markets

no code implementations14 Dec 2020 Lydia T. Liu, Feng Ruan, Horia Mania, Michael I. Jordan

We study two-sided matching markets in which one side of the market (the players) does not have a priori knowledge about its preferences for the other side (the arms) and is required to learn its preferences from experience.

Active Learning for Nonlinear System Identification with Guarantees

no code implementations18 Jun 2020 Horia Mania, Michael. I. Jordan, Benjamin Recht

While the identification of nonlinear dynamical systems is a fundamental building block of model-based reinforcement learning and feedback control, its sample complexity is only understood for systems that either have discrete states and actions or for systems that can be identified from data generated by i. i. d.

Active Learning Model-based Reinforcement Learning +1

Competing Bandits in Matching Markets

no code implementations12 Jun 2019 Lydia T. Liu, Horia Mania, Michael. I. Jordan

Stable matching, a classical model for two-sided markets, has long been studied with little consideration for how each side's preferences are learned.

Multi-Armed Bandits

Model Similarity Mitigates Test Set Overuse

no code implementations NeurIPS 2019 Horia Mania, John Miller, Ludwig Schmidt, Moritz Hardt, Benjamin Recht

Excessive reuse of test data has become commonplace in today's machine learning workflows.

Certainty Equivalence is Efficient for Linear Quadratic Control

no code implementations NeurIPS 2019 Horia Mania, Stephen Tu, Benjamin Recht

We show that for both the fully and partially observed settings, the sub-optimality gap between the cost incurred by playing the certainty equivalent controller on the true system and the cost incurred by using the optimal LQ controller enjoys a fast statistical rate, scaling as the square of the parameter error.

Simple random search of static linear policies is competitive for reinforcement learning

no code implementations NeurIPS 2018 Horia Mania, Aurelia Guy, Benjamin Recht

Common evaluation methodology shows that our method matches state-of-the-art sample efficiency on the benchmark MuJoCo locomotion tasks.

Continuous Control reinforcement-learning

Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator

no code implementations NeurIPS 2018 Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

We consider adaptive control of the Linear Quadratic Regulator (LQR), where an unknown linear system is controlled subject to quadratic costs.

Simple random search provides a competitive approach to reinforcement learning

24 code implementations19 Mar 2018 Horia Mania, Aurelia Guy, Benjamin Recht

A common belief in model-free reinforcement learning is that methods based on random search in the parameter space of policies exhibit significantly worse sample complexity than those that explore the space of actions.

Continuous Control reinforcement-learning

Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification

no code implementations22 Feb 2018 Max Simchowitz, Horia Mania, Stephen Tu, Michael. I. Jordan, Benjamin Recht

We prove that the ordinary least-squares (OLS) estimator attains nearly minimax optimal performance for the identification of linear dynamical systems from a single observed trajectory.

Time Series

On the Sample Complexity of the Linear Quadratic Regulator

no code implementations4 Oct 2017 Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

This paper addresses the optimal control problem known as the Linear Quadratic Regulator in the case when the dynamics are unknown.

On kernel methods for covariates that are rankings

no code implementations25 Mar 2016 Horia Mania, Aaditya Ramdas, Martin J. Wainwright, Michael. I. Jordan, Benjamin Recht

This paper studies the use of reproducing kernel Hilbert space methods for learning from permutation-valued features.

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization

no code implementations24 Jul 2015 Horia Mania, Xinghao Pan, Dimitris Papailiopoulos, Benjamin Recht, Kannan Ramchandran, Michael. I. Jordan

We demonstrate experimentally on a 16-core machine that the sparse and parallel version of SVRG is in some cases more than four orders of magnitude faster than the standard SVRG algorithm.

Stochastic Optimization

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