Search Results for author: Luis E. Ortiz

Found 9 papers, 0 papers with code

Correlated Equilibria for Approximate Variational Inference in MRFs

no code implementations10 Apr 2016 Luis E. Ortiz, Boshen Wang, Ze Gong

Almost all of the work in graphical models for game theory has mirrored previous work in probabilistic graphical models.

Fairness Variational Inference

Some Open Problems in Optimal AdaBoost and Decision Stumps

no code implementations26 May 2015 Joshua Belanich, Luis E. Ortiz

Answers to the open problems can have immediate significant impact to (1) cementing previously established results on asymptotic convergence properties of Optimal AdaBoost, for finite datasets, which in turn can be the start to any convergence-rate analysis; (2) understanding the weak-hypotheses class of effective decision stumps generated from data, which we have empirically observed to be significantly smaller than the typically obtained class, as well as the effect on the weak learner's running time and previously established improved bounds on the generalization performance of Optimal AdaBoost classifiers; and (3) shedding some light on the "self control" that AdaBoost tends to exhibit in practice.

Binary Classification

Graphical Potential Games

no code implementations6 May 2015 Luis E. Ortiz

This note provides several characterizations of graphical potential games by leveraging well-known results from the literature on probabilistic graphical models.

Image Segmentation Semantic Segmentation

Computing Nash Equilibria in Generalized Interdependent Security Games

no code implementations NeurIPS 2014 Hau Chan, Luis E. Ortiz

Like traditional IDS games, originally introduced by economists and risk-assessment experts Heal and Kunreuther about a decade ago, generalized IDS games model agents’ voluntary investment decisions when facing potential direct risk and transfer risk exposure from other agents.

Causal Strategic Inference in Networked Microfinance Economies

no code implementations NeurIPS 2014 Mohammad T. Irfan, Luis E. Ortiz

For a special case of our model, we show that an equilibrium point always exists and that the equilibrium interest rates are unique.

On Sparse Discretization for Graphical Games

no code implementations12 Nov 2014 Luis E. Ortiz

This short paper concerns discretization schemes for representing and computing approximate Nash equilibria, with emphasis on graphical games, but briefly touching on normal-form and poly-matrix games.

On the Convergence Properties of Optimal AdaBoost

no code implementations5 Dec 2012 Joshua Belanich, Luis E. Ortiz

We provide constructive proofs of several arbitrarily accurate approximations of Optimal AdaBoost; prove that they exhibit certain cycling behavior in finite time, and that the resulting dynamical system is ergodic; and establish sufficient conditions for the same to hold for the actual Optimal-AdaBoost update.

BIG-bench Machine Learning

Sparse and Locally Constant Gaussian Graphical Models

no code implementations NeurIPS 2009 Jean Honorio, Dimitris Samaras, Nikos Paragios, Rita Goldstein, Luis E. Ortiz

Locality information is crucial in datasets where each variable corresponds to a measurement in a manifold (silhouettes, motion trajectories, 2D and 3D images).

CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation

no code implementations NeurIPS 2007 Luis E. Ortiz

This paper proposes constraint propagation relaxation (CPR), a probabilistic approach to classical constraint propagation that provides another view on the whole parametric family of survey propagation algorithms SP(ρ), ranging from belief propagation (ρ = 0) to (pure) survey propagation(ρ = 1).

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