
Joint Gaussian Graphical Model Estimation: A Survey
Graphs from complex systems often share a partial underlying structure a...
read it

Secure ByzantineRobust Distributed Learning via Clustering
Federated learning systems that jointly preserve Byzantine robustness an...
read it

Optimizing Blackbox Metrics with Iterative Example Weighting
We consider learning to optimize a classification metric defined by a bl...
read it

Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation
Controllable semantic image editing enables a user to change entire imag...
read it

A Nonconvex Framework for Structured Dynamic Covariance Recovery
We propose a flexible yet interpretable model for highdimensional data ...
read it

Quadratic Metric Elicitation with Application to Fairness
Metric elicitation is a recent framework for eliciting performance metri...
read it

CSER: Communicationefficient SGD with Error Reset
The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
read it

Bayesian Coresets: An Optimization Perspective
Bayesian coresets have emerged as a promising approach for implementing ...
read it

Does Adversarial Transferability Indicate Knowledge Transferability?
Despite the immense success that deep neural networks (DNNs) have achiev...
read it

Fair Performance Metric Elicitation
What is a fair performance metric? We consider the choice of fairness me...
read it

RichItem Recommendations for RichUsers via GCNN: Exploiting Dynamic and Static Side Information
We study the standard problem of recommending relevant items to users; a...
read it

Towards A Controllable Disentanglement Network
This paper addresses two crucial problems of learning disentangled image...
read it

Learning Controllable Disentangled Representations with Decorrelation Regularization
A crucial problem in learning disentangled image representations is cont...
read it

Local AdaAlter: CommunicationEfficient Stochastic Gradient Descent with Adaptive Learning Rates
Recent years have witnessed the growth of largescale distributed machin...
read it

Learning Sparse Distributions using Iterative Hard Thresholding
Iterative hard thresholding (IHT) is a projected gradient descent algori...
read it

Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Differential graphical models are designed to represent the difference b...
read it

Consistent Classification with Generalized Metrics
We propose a framework for constructing and analyzing multiclass and mul...
read it

Towards Realistic Individual Recourse and Actionable Explanations in BlackBox Decision Making Systems
Machine learning based decision making systems are increasingly affectin...
read it

Partially Linear Additive Gaussian Graphical Models
We propose a partially linear additive Gaussian graphical model (PLAGGM...
read it

Clustered Monotone Transforms for Rating Factorization
Exploiting lowrank structure of the useritem rating matrix has been th...
read it

Interpreting Black Box Predictions using Fisher Kernels
Research in both machine learning and psychology suggests that salient e...
read it

Joint Nonparametric Precision Matrix Estimation with Confounding
We consider the problem of precision matrix estimation where, due to ext...
read it

xGEMs: Generating Examplars to Explain BlackBox Models
This work proposes xGEMs or manifold guided exemplars, a framework to un...
read it

Eliciting Binary Performance Metrics
Given a binary prediction problem, which performance metric should the c...
read it

Binary Classification with Karmic, ThresholdQuasiConcave Metrics
Complex performance measures, beyond the popular measure of accuracy, ar...
read it

Zeno: Byzantinesuspicious stochastic gradient descent
We propose Zeno, a new robust aggregation rule, for distributed synchron...
read it

Phocas: dimensional Byzantineresilient stochastic gradient descent
We propose a novel robust aggregation rule for distributed synchronous S...
read it

Generalized Byzantinetolerant SGD
We propose three new robust aggregation rules for distributed synchronou...
read it

Dependent relevance determination for smooth and structured sparse regression
In many problem settings, parameter vectors are not merely sparse, but d...
read it

Preference Completion from Partial Rankings
We propose a novel and efficient algorithm for the collaborative prefere...
read it

Online Classification with Complex Metrics
We present a framework and analysis of consistent binary classification ...
read it

Information Projection and Approximate Inference for Structured Sparse Variables
Approximate inference via information projection has been recently intro...
read it

A simple and provable algorithm for sparse diagonal CCA
Given two sets of variables, derived from a common set of samples, spars...
read it

Generalized Linear Models for Aggregated Data
Databases in domains such as healthcare are routinely released to the pu...
read it

Optimal DecisionTheoretic Classification Using NonDecomposable Performance Metrics
We provide a general theoretical analysis of expected outofsample util...
read it

A Constrained MatrixVariate Gaussian Process for Transposable Data
Transposable data represents interactions among two sets of entities, an...
read it

Constrained Bayesian Inference for Low Rank Multitask Learning
We present a novel approach for constrained Bayesian inference. Unlike c...
read it

The trace norm constrained matrixvariate Gaussian process for multitask bipartite ranking
We propose a novel hierarchical model for multitask bipartite ranking. T...
read it

Learning to Rank With Bregman Divergences and Monotone Retargeting
This paper introduces a novel approach for learning to rank (LETOR) base...
read it
Oluwasanmi Koyejo
is this you? claim profile
Assistant Professor Department of Computer Science at University of Illinois at UrbanaChampaign