DeepAI

University of New Hampshire

∙ Durham , United States ∙ 0 followers

The University of New Hampshire is a public research university with its main campus in Durham, New Hampshire.

Featured Researchers

Chris Amato
42 publications
Marek Petrik
27 publications
HaiYing Wang
24 publications
Reazul Hasan Russel
9 publications
Aleksey Charapko
8 publications
Laura Dietz
4 publications
Jeremiah W. Johnson
4 publications
Jeremiah Johnson
2 publications
Per Berglund
2 publications
Jia Lin Hau
1 publication
Mostafa Hussein
1 publication

∙ 07/24/2020

Bayesian Robust Optimization for Imitation Learning

One of the main challenges in imitation learning is determining what act...

Daniel S. Brown, et al. ∙

∙ 04/30/2019

Structured Prediction using cGANs with Fusion Discriminator

We propose the fusion discriminator, a single unified framework for inco...

Faisal, et al. ∙

∙ 09/21/2022

On the convex formulations of robust Markov decision processes

Robust Markov decision processes (MDPs) are used for applications of dyn...

Julien Grand-Clément, et al. ∙

∙ 11/16/2016

Neural Style Representations and the Large-Scale Classification of Artistic Style

The artistic style of a painting is a subtle aesthetic judgment used by ...

Jeremiah Johnson, et al. ∙

∙ 09/09/2022

RASR: Risk-Averse Soft-Robust MDPs with EVaR and Entropic Risk

Prior work on safe Reinforcement Learning (RL) has studied risk-aversion...

Jia Lin Hau, et al. ∙

∙ 05/27/2022

Robust Phi-Divergence MDPs

In recent years, robust Markov decision processes (MDPs) have emerged as...

Chin Pang Ho, et al. ∙

∙ 12/16/2021

Machine Learning Kreuzer–Skarke Calabi–Yau Threefolds

Using a fully connected feedforward neural network we study topological ...

Per Berglund, et al. ∙

∙ 09/28/2021

A Contrastive Learning Approach to Auroral Identification and Classification

Unsupervised learning algorithms are beginning to achieve accuracies com...

Jeremiah W. Johnson, et al. ∙

∙ 01/04/2021

Robust Maximum Entropy Behavior Cloning

Imitation learning (IL) algorithms use expert demonstrations to learn a ...

Mostafa Hussein, et al. ∙

∙ 08/06/2020

Fast Flexible Paxos: Relaxing Quorum Intersection for Fast Paxos

Paxos, the de facto standard approach to solving distributed consensus, ...

Heidi Howard, et al. ∙

∙ 12/04/2019

A Probabilistic Approach to Satisfiability of Propositional Logic Formulae

We propose a version of WalkSAT algorithm, named as BetaWalkSAT. This me...

Reazul Hasan Russel, et al. ∙

∙ 04/17/2019

Robust Exploration with Tight Bayesian Plausibility Sets

Optimism about the poorly understood states and actions is the main driv...

Reazul H. Russel, et al. ∙

∙ 01/21/2019

A Short Survey on Probabilistic Reinforcement Learning

A reinforcement learning agent tries to maximize its cumulative payoff b...

Reazul Hasan Russel, et al. ∙

∙ 01/03/2019

Subspace Match Probably Does Not Accurately Assess the Similarity of Learned Representations

Learning informative representations of data is one of the primary goals...

Jeremiah Johnson, et al. ∙

∙ 05/01/2018

Adapting Mask-RCNN for Automatic Nucleus Segmentation

Automatic segmentation of microscopy images is an important task in medi...

Jeremiah W. Johnson, et al. ∙

∙ 05/01/2018

On the Equivalence of Generative and Discriminative Formulations of the Sequential Dependence Model

The sequential dependence model (SDM) is a popular retrieval model which...

Laura Dietz, et al. ∙

∙ 05/03/2016

Blackbox: A procedure for parallel optimization of expensive black-box functions

This note provides a description of a procedure that is designed to effi...

Paul Knysh, et al. ∙

∙ 05/01/2015

Stick-Breaking Policy Learning in Dec-POMDPs

Expectation maximization (EM) has recently been shown to be an efficient...

Miao Liu, et al. ∙

∙ 02/03/2017

Optimal Subsampling for Large Sample Logistic Regression

For massive data, the family of subsampling algorithms is popular to dow...

HaiYing Wang, et al. ∙