Lista de obras -

A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery

artículo científico publicado en 2016

A Dirty Model for Multi-task Learning ⬇️

A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation ⬇️

artículo científico publicado en 2012

A Representation Theory for Ranking Functions ⬇️

artículo científico publicado en 2014

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution

artículo científico publicado en 2017

A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers ⬇️

artículo científico publicado en 2009

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables ⬇️

Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs

artículo científico publicado en 2015

Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs ⬇️

Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs ⬇️

artículo científico publicado en 2014

Closed-form Estimators for High-dimensional Generalized Linear Models ⬇️

Collaborative Filtering with Graph Information: Consistency and Scalable Methods ⬇️

Conditional Random Fields via Univariate Exponential Families ⬇️

Connecting Optimization and Regularization Paths ⬇️

Consistent Binary Classification with Generalized Performance Metrics ⬇️

artículo científico publicado en 2014

Consistent Multilabel Classification ⬇️

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings ⬇️

artículo científico publicado en 2014

DAGs with NO TEARS: Continuous Optimization for Structure Learning ⬇️

Dirty Statistical Models ⬇️

Dual Decomposed Learning with Factorwise Oracles for Structural SVM of Large Output Domain ⬇️

artículo científico publicado en 2016

ENCODING AND DECODING V1 FMRI RESPONSES TO NATURAL IMAGES WITH SPARSE NONPARAMETRIC MODELS.

artículo científico publicado en 2011

Elementary Estimators for Graphical Models ⬇️

artículo científico publicado en 2014

Fast Classification Rates for High-dimensional Gaussian Generative Models ⬇️

Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial ⬇️

Game Design for Eliciting Distinguishable Behavior ⬇️

Graphical Models via Generalized Linear Models ⬇️

artículo científico publicado en 2012

Graphical Models via Univariate Exponential Family Distributions

artículo científico publicado en 2015

Greedy Algorithms for Structurally Constrained High Dimensional Problems ⬇️

artículo científico publicado en 2011

Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain

artículo científico publicado en 2017

High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression ⬇️

artículo científico publicado en 2007

Information-theoretic lower bounds on the oracle complexity of convex optimization ⬇️

artículo científico publicado en 2009

Large Scale Distributed Sparse Precision Estimation ⬇️

Learning with Noisy Labels ⬇️

MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization ⬇️

Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of ℓ1-regularized MLE ⬇️

artículo científico publicado en 2009

Nearest Neighbor based Greedy Coordinate Descent ⬇️

artículo científico publicado en 2011

Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images ⬇️

article by Vincent Q. Vu et al published 2009 in Advances in Neural Information Processing Systems 21

On Human-Aligned Risk Minimization ⬇️

artículo científico publicado en 2019

On Learning Discrete Graphical Models using Greedy Methods ⬇️

artículo científico publicado en 2011

On Poisson Graphical Models ⬇️

On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models ⬇️

artículo científico publicado en 2017

On the (In)fidelity and Sensitivity of Explanations ⬇️

artículo científico publicado en 2019

On the Information Theoretic Limits of Learning Ising Models ⬇️

artículo científico publicado en 2014

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation ⬇️

Preconditioner Approximations for Probabilistic Graphical Models ⬇️

artículo científico publicado en 2006

Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli

artículo científico publicado en 2014

Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators ⬇️

artículo científico publicado en 2014

QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models ⬇️

artículo científico publicado en 2014

Representer Point Selection for Explaining Deep Neural Networks ⬇️

SHAPE BASED IMAGE RECONSTRUCTION USING LINEARIZED DEFORMATIONS.

artículo científico publicado en 2017

Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition

artículo científico publicado en 2017

SpAM: Sparse Additive Models ⬇️

artículo científico publicado en 2008

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation ⬇️

artículo científico publicado en 2011

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent ⬇️

Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space ⬇️

artículo científico publicado en 2014

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

artículo científico publicado en 2016

The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities ⬇️

artículo científico publicado en 2017

Lista de obras de

A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery

A Dirty Model for Multi-task Learning ⬇️

A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation ⬇️

A Representation Theory for Ranking Functions ⬇️

A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution

A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers ⬇️

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables ⬇️

Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs

Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs ⬇️

Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs ⬇️

Closed-form Estimators for High-dimensional Generalized Linear Models ⬇️

Collaborative Filtering with Graph Information: Consistency and Scalable Methods ⬇️

Conditional Random Fields via Univariate Exponential Families ⬇️

Connecting Optimization and Regularization Paths ⬇️

Consistent Binary Classification with Generalized Performance Metrics ⬇️

Consistent Multilabel Classification ⬇️

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings ⬇️

DAGs with NO TEARS: Continuous Optimization for Structure Learning ⬇️

Dirty Statistical Models ⬇️

Dual Decomposed Learning with Factorwise Oracles for Structural SVM of Large Output Domain ⬇️

ENCODING AND DECODING V1 FMRI RESPONSES TO NATURAL IMAGES WITH SPARSE NONPARAMETRIC MODELS.

Elementary Estimators for Graphical Models ⬇️

Fast Classification Rates for High-dimensional Gaussian Generative Models ⬇️

Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial ⬇️

Game Design for Eliciting Distinguishable Behavior ⬇️

Graphical Models via Generalized Linear Models ⬇️

Graphical Models via Univariate Exponential Family Distributions

Greedy Algorithms for Structurally Constrained High Dimensional Problems ⬇️

Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain

High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression ⬇️

Information-theoretic lower bounds on the oracle complexity of convex optimization ⬇️

Large Scale Distributed Sparse Precision Estimation ⬇️

Learning with Noisy Labels ⬇️

MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization ⬇️

Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of ℓ1-regularized MLE ⬇️

Nearest Neighbor based Greedy Coordinate Descent ⬇️

Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images ⬇️

On Human-Aligned Risk Minimization ⬇️

On Learning Discrete Graphical Models using Greedy Methods ⬇️

On Poisson Graphical Models ⬇️

On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models ⬇️

On the (In)fidelity and Sensitivity of Explanations ⬇️

On the Information Theoretic Limits of Learning Ising Models ⬇️

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation ⬇️

Preconditioner Approximations for Probabilistic Graphical Models ⬇️

Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli

Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators ⬇️

QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models ⬇️

Representer Point Selection for Explaining Deep Neural Networks ⬇️

SHAPE BASED IMAGE RECONSTRUCTION USING LINEARIZED DEFORMATIONS.

Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition

SpAM: Sparse Additive Models ⬇️

Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation ⬇️

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent ⬇️

Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space ⬇️

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities ⬇️

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models ⬇️