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05/27/2023
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models
Deep neural networks (DNNs) lack the precise semantics and definitive pr...
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02/23/2023
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference
Our goal is to produce methods for observational causal inference that a...
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03/19/2021
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach
Predicting and discovering drug-drug interactions (DDIs) using machine l...
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11/18/2020
High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records
Accurate estimation of healthcare costs is crucial for healthcare system...
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05/12/2020
Temporal Poisson Square Root Graphical Models
We propose temporal Poisson square root graphical models (TPSQRs), a gen...
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05/12/2020
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error
We study the L_1-regularized maximum likelihood estimator/estimation (ML...
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02/18/2020
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods
We study the problem of learning Granger causality between event types f...
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12/07/2019
AutoBlock: A Hands-off Blocking Framework for Entity Matching
Entity matching seeks to identify data records over one or multiple data...
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11/14/2019
Predicting Drug-Drug Interactions from Molecular Structure Images
Predicting and discovering drug-drug interactions (DDIs) is an important...
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07/03/2019
High-Throughput Machine Learning from Electronic Health Records
The widespread digitization of patient data via electronic health record...
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06/12/2019
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
We present a simple text mining method that is easy to implement, requir...
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05/06/2019
Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered Tissues
There is a growing need for fast and accurate methods for testing develo...
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11/21/2018
Privacy-Preserving Collaborative Prediction using Random Forests
We study the problem of privacy-preserving machine learning (PPML) for e...
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10/02/2018
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge
Hexoses are simple sugars that play a key role in many cellular pathways...
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02/27/2017
An Efficient Pseudo-likelihood Method for Sparse Binary Pairwise Markov Network Estimation
The pseudo-likelihood method is one of the most popular algorithms for l...
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04/20/2016
Computational Drug Repositioning Using Continuous Self-controlled Case Series
Computational Drug Repositioning (CDR) is the task of discovering potent...
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10/19/2012
CLP(BN): Constraint Logic Programming for Probabilistic Knowledge
We present CLP(BN), a novel approach that aims at expressing Bayesian ne...
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06/27/2012
Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events
Learning from electronic medical records (EMR) is challenging due to the...
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06/18/2012