
Biomedical Interpretable Entity Representations
Pretrained language models induce dense entity representations that off...
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Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
Many reallife applications involve simultaneously forecasting multiple ...
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Biased Models Have Biased Explanations
We study fairness in Machine Learning (FairML) through the lens of attri...
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FaiRN: Fair and Robust Neural Networks for Structured Data
Fairness in machine learning is crucial when individuals are subject to ...
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Explainable Machine Learning in Deployment
Explainable machine learning seeks to provide various stakeholders with ...
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Vehicular Multiobject Tracking with Persistent Detector Failures
Autonomous vehicles often perceive the environment by feeding sensor dat...
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Towards Realistic Individual Recourse and Actionable Explanations in BlackBox Decision Making Systems
Machine learning based decision making systems are increasingly affectin...
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Learning More From Less: Towards Strengthening Weak Supervision for AdHoc Retrieval
The limited availability of ground truth relevance labels has been a maj...
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On Single Source Robustness in Deep Fusion Models
Algorithms that fuse multiple input sources benefit from both complement...
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CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models
As artificial intelligence plays an increasingly important role in our s...
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Explaining Deep Classification of TimeSeries Data with Learned Prototypes
The emergence of deep learning networks raises a need for algorithms to ...
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Interpreting Black Box Predictions using Fisher Kernels
Research in both machine learning and psychology suggests that salient e...
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PIVETedGranite: Computational Phenotypes through Constrained Tensor Factorization
It has been recently shown that sparse, nonnegative tensor factorization...
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xGEMs: Generating Examplars to Explain BlackBox Models
This work proposes xGEMs or manifold guided exemplars, a framework to un...
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Measurementwise Occlusion in Multiobject Tracking
Handling object interaction is a fundamental challenge in practical mult...
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Nonparametric Bayesian Sparse Graph Linear Dynamical Systems
A nonparametric Bayesian sparse graph linear dynamical system (SGLDS) is...
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Relaxed Oracles for SemiSupervised Clustering
Pairwise "samecluster" queries are one of the most widely used forms of...
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SemiSupervised Active Clustering with Weak Oracles
Semisupervised active clustering (SSAC) utilizes the knowledge of a dom...
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Optimal Alarms for Vehicular Collision Detection
An important application of intelligent vehicles is advance detection of...
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Boosting Variational Inference: an Optimization Perspective
Variational Inference is a popular technique to approximate a possibly i...
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Scalable Greedy Feature Selection via Weak Submodularity
Greedy algorithms are widely used for problems in machine learning such ...
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Graphical RNN Models
Many time series are generated by a set of entities that interact with o...
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Preference Completion from Partial Rankings
We propose a novel and efficient algorithm for the collaborative prefere...
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Identifiable Phenotyping using Constrained NonNegative Matrix Factorization
This work proposes a new algorithm for automated and simultaneous phenot...
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Information Projection and Approximate Inference for Structured Sparse Variables
Approximate inference via information projection has been recently intro...
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ACDC: αCarving Decision Chain for Risk Stratification
In many healthcare settings, intuitive decision rules for risk stratific...
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Generalized Linear Models for Aggregated Data
Databases in domains such as healthcare are routinely released to the pu...
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Monotone Retargeting for Unsupervised Rank Aggregation with Object Features
Learning the true ordering between objects by aggregating a set of exper...
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Unified View of Matrix Completion under General Structural Constraints
In this paper, we present a unified analysis of matrix completion under ...
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Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices
A gamma process dynamic Poisson factor analysis model is proposed to fac...
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Exponential Family Matrix Completion under Structural Constraints
We consider the matrix completion problem of recovering a structured mat...
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A Constrained MatrixVariate Gaussian Process for Transposable Data
Transposable data represents interactions among two sets of entities, an...
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Perturbed Gibbs Samplers for Synthetic Data Release
We propose a categorical data synthesizer with a quantifiable disclosure...
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Constrained Bayesian Inference for Low Rank Multitask Learning
We present a novel approach for constrained Bayesian inference. Unlike c...
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The trace norm constrained matrixvariate Gaussian process for multitask bipartite ranking
We propose a novel hierarchical model for multitask bipartite ranking. T...
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Probabilistic Combination of Classifier and Cluster Ensembles for Nontransductive Learning
Unsupervised models can provide supplementary soft constraints to help c...
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Dating Texts without Explicit Temporal Cues
This paper tackles temporal resolution of documents, such as determining...
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Learning to Rank With Bregman Divergences and Monotone Retargeting
This paper introduces a novel approach for learning to rank (LETOR) base...
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A PrivacyAware Bayesian Approach for Combining Classifier and Cluster Ensembles
This paper introduces a privacyaware Bayesian approach that combines en...
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Robust Combining of Disparate Classifiers through Order Statistics
Integrating the outputs of multiple classifiers via combiners or metale...
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Linear and Order Statistics Combiners for Pattern Classification
Several researchers have experimentally shown that substantial improveme...
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Ensembles of Radial Basis Function Networks for Spectroscopic Detection of Cervical PreCancer
The mortality related to cervical cancer can be substantially reduced th...
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Joydeep Ghosh
verfied profile
Professor, Schlumberger Centennial Chair in Electrical Engineering at The University of Texas at Austin and Chief Scientist at Cognitivescale