Search Results for author: Luiz. F. O. Chamon

Found 12 papers, 0 papers with code

Probably Approximately Correct Constrained Learning

no code implementations NeurIPS 2020 Luiz. F. O. Chamon, Alejandro Ribeiro

To overcome this issue, we prove that under mild conditions the empirical dual problem of constrained learning is also a PAC constrained learner that now leads to a practical constrained learning algorithm based solely on solving unconstrained problems.

PAC learning Robust classification

Graphon Neural Networks and the Transferability of Graph Neural Networks

no code implementations NeurIPS 2020 Luana Ruiz, Luiz. F. O. Chamon, Alejandro Ribeiro

These graph convolutions combine information from adjacent nodes using coefficients that are shared across all nodes.

The empirical duality gap of constrained statistical learning

no code implementations12 Feb 2020 Luiz. F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro

This paper is concerned with the study of constrained statistical learning problems, the unconstrained version of which are at the core of virtually all of modern information processing.

Risk-Aware MMSE Estimation

no code implementations6 Dec 2019 Dionysios S. Kalogerias, Luiz. F. O. Chamon, George J. Pappas, Alejandro Ribeiro

Despite the simplicity and intuitive interpretation of Minimum Mean Squared Error (MMSE) estimators, their effectiveness in certain scenarios is questionable.

Constrained Reinforcement Learning Has Zero Duality Gap

no code implementations NeurIPS 2019 Santiago Paternain, Luiz. F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro

The later is generally addressed by formulating the conflicting requirements as a constrained RL problem and solved using Primal-Dual methods.

reinforcement-learning Reinforcement Learning (RL)

Sparse multiresolution representations with adaptive kernels

no code implementations7 May 2019 Maria Peifer, Luiz. F. O. Chamon, Santiago Paternain, Alejandro Ribeiro

To address the complexity issues, we then write the function estimation problem as a sparse functional program that explicitly minimizes the support of the representation leading to low complexity solutions.

Functional Nonlinear Sparse Models

no code implementations1 Nov 2018 Luiz. F. O. Chamon, Yonina C. Eldar, Alejandro Ribeiro

Even if they are, recovering sparse solutions using convex relaxations requires assumptions that may be hard to meet in practice.

Robust classification Spectrum Cartography +1

Learning Optimal Resource Allocations in Wireless Systems

no code implementations21 Jul 2018 Mark Eisen, Clark Zhang, Luiz. F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro

This paper considers the design of optimal resource allocation policies in wireless communication systems which are generically modeled as a functional optimization problem with stochastic constraints.

Greedy Sampling of Graph Signals

no code implementations5 Apr 2017 Luiz. F. O. Chamon, Alejandro Ribeiro

In contrast to traditional signal processing, the irregularity of the signal domain makes selecting a sampling set non-trivial and hard to analyze.

Video Compression

Combination of LMS Adaptive Filters with Coefficients Feedback

no code implementations10 Aug 2016 Luiz. F. O. Chamon, Cassio G. Lopes

Parallel combinations of adaptive filters have been effectively used to improve the performance of adaptive algorithms and address well-known trade-offs, such as convergence rate vs. steady-state error.

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