Indiana University

research

∙ 12/17/2019

srlearn: A Python Library for Gradient-Boosted Statistical Relational Models

We present srlearn, a Python library for boosted statistical relational ...

Alexander L. Hayes, et al. ∙

research

∙ 01/04/2019

Accelerating Goal-Directed Reinforcement Learning by Model Characterization

We propose a hybrid approach aimed at improving the sample efficiency in...

Shoubhik Debnath, et al. ∙

research

∙ 11/12/2019

Scientific Image Restoration Anywhere

The use of deep learning models within scientific experimental facilitie...

Vibhatha Abeykoon, et al. ∙

research

∙ 06/04/2020

A Computational Model of Early Word Learning from the Infant's Point of View

Human infants have the remarkable ability to learn the associations betw...

Satoshi Tsutsui, et al. ∙

research

∙ 08/26/2019

Bayesian Nonparametrics for Non-exhaustive Learning

Non-exhaustive learning (NEL) is an emerging machine-learning paradigm d...

Yicheng Cheng, et al. ∙

research

∙ 07/27/2021

HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks

Data-intensive applications impact many domains, and their steadily incr...

Supun Kamburugamuve, et al. ∙

research

∙ 11/16/2019

Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data

Big data is one of the cornerstones to enabling and training deep neural...

Qian Lou, et al. ∙

research

∙ 10/14/2021

Residual2Vec: Debiasing graph embedding with random graphs

Graph embedding maps a graph into a convenient vector-space representati...

Sadamori Kojaku, et al. ∙

research

∙ 11/08/2021

The Global Structure of Codimension-2 Local Bifurcations in Continuous-Time Recurrent Neural Networks

If we are ever to move beyond the study of isolated special cases in the...

Randall D. Beer, et al. ∙

research

∙ 06/03/2020

Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes

We propose a principled kernel-based policy iteration algorithm to solve...

Junhong Xu, et al. ∙

research

∙ 01/04/2019

Solving Markov Decision Processes with Reachability Characterization from Mean First Passage Times

A new mechanism for efficiently solving the Markov decision processes (M...

Shoubhik Debnath, et al. ∙

research

∙ 10/22/2018

Actor-Expert: A Framework for using Action-Value Methods in Continuous Action Spaces

Value-based approaches can be difficult to use in continuous action spac...

Sungsu Lim, et al. ∙

research

∙ 06/03/2020

Generalized Penalty for Circular Coordinate Representation

Topological Data Analysis (TDA) provides novel approaches that allow us ...

Hengrui Luo, et al. ∙

research

∙ 06/01/2022

Assessing Group-level Gender Bias in Professional Evaluations: The Case of Medical Student End-of-Shift Feedback

Although approximately 50 female physicians tend to be underrepresented ...

Emmy Liu, et al. ∙

research

∙ 04/12/2020

Simulating Molecular Dynamics with Large Timesteps using Recurrent Neural Networks

Molecular dynamics simulations rely on numerical integrators such as Ver...

JCS Kadupitiya, et al. ∙

research

∙ 07/31/2020

Geometric All-Way Boolean Tensor Decomposition

Boolean tensor has been broadly utilized in representing high dimensiona...

Changlin Wan, et al. ∙

research

∙ 10/29/2021

Polyline Based Generative Navigable Space Segmentation for Autonomous Visual Navigation

Detecting navigable space is a fundamental capability for mobile robots ...

Zheng Chen, et al. ∙

research

∙ 06/12/2018

Organizing Experience: A Deeper Look at Replay Mechanisms for Sample-based Planning in Continuous State Domains

Model-based strategies for control are critical to obtain sample efficie...

Yangchen Pan, et al. ∙

research

∙ 08/18/2018

Support Neighbor Loss for Person Re-Identification

Person re-identification (re-ID) has recently been tremendously boosted ...

Kai Li, et al. ∙

research

∙ 09/09/2019

MEBF: a fast and efficient Boolean matrix factorization method

Boolean matrix has been used to represent digital information in many fi...

Changlin Wan, et al. ∙

research

∙ 01/12/2021

People, Places, and Ties: Landscape of social places and their social network structures

Due to their essential role as places for socialization, "third places" ...

Jaehyuk Park, et al. ∙

research

∙ 08/15/2022

Action Recognition based on Cross-Situational Action-object Statistics

Machine learning models of visual action recognition are typically train...

Satoshi Tsutsui, et al. ∙

research

∙ 05/14/2020

Domain Conditioned Adaptation Network

Tremendous research efforts have been made to thrive deep domain adaptat...

Shuang Li, et al. ∙

research

∙ 03/02/2017

Using Synthetic Data to Train Neural Networks is Model-Based Reasoning

We draw a formal connection between using synthetic training data to opt...

Tuan Anh Le, et al. ∙

research

∙ 03/06/2016

Composing inference algorithms as program transformations

Probabilistic inference procedures are usually coded painstakingly from ...

Robert Zinkov, et al. ∙

research

∙ 01/14/2016

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

Link prediction, or predicting the likelihood of a link in a knowledge g...

Baichuan Zhang, et al. ∙

research

∙ 12/23/2015

Incremental Method for Spectral Clustering of Increasing Orders

The smallest eigenvalues and the associated eigenvectors (i.e., eigenpai...

Pin-Yu Chen, et al. ∙

research

∙ 11/29/2017

Predicting and Explaining Human Semantic Search in a Cognitive Model

Recent work has attempted to characterize the structure of semantic memo...

Filip Miscevic, et al. ∙

research

∙ 06/26/2017

The Minor Fall, the Major Lift: Inferring Emotional Valence of Musical Chords through Lyrics

We investigate the association between musical chords and lyrics by anal...

Artemy Kolchinsky, et al. ∙

research

∙ 11/20/2016

Gendered Conversation in a Social Game-Streaming Platform

Online social media and games are increasingly replacing offline social ...

Supun Nakandala, et al. ∙

research

∙ 01/29/2018

On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising

We present a psychoacoustically enhanced cost function to balance networ...

Kai Zhen, et al. ∙

research

∙ 02/04/2018

Smooth q-Gram, and Its Applications to Detection of Overlaps among Long, Error-Prone Sequencing Reads

We propose smooth q-gram, the first variant of q-gram that captures q-gr...

Haoyu Zhang, et al. ∙

research

∙ 02/12/2018

Scalable Downward Routing for Wireless Sensor Networks and Internet of Things Actuation

In this paper, we study the downward routing for network control/actuati...

Xiaoyang Zhong, et al. ∙

research

∙ 03/11/2018

Learning Partially Structured Environmental Dynamics for Marine Robotic Navigation

We investigate the scenario that a robot needs to reach a designated goa...

Chen Huang, et al. ∙

research

∙ 03/14/2018

PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning

One of the most exciting advancements in AI over the last decade is the ...

Tao Liu, et al. ∙

research

∙ 03/14/2018

DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

As one of most fascinating machine learning techniques, deep neural netw...

Zihao Liu, et al. ∙

research

∙ 04/25/2018

Hierarchical RNN for Information Extraction from Lawsuit Documents

Every lawsuit document contains the information about the party's claim,...

Xi Rao, et al. ∙

research

∙ 04/25/2018

High-Performance Massive Subgraph Counting using Pipelined Adaptive-Group Communication

Subgraph counting aims to count the number of occurrences of a subgraph ...

Langshi Chen, et al. ∙

research

∙ 05/23/2018

Tight Bounds for Collaborative PAC Learning via Multiplicative Weights

We study the collaborative PAC learning problem recently proposed in Blu...

Jiecao Chen, et al. ∙

research

∙ 05/25/2018

How Many Machines Can We Use in Parallel Computing for Kernel Ridge Regression?

This paper attempts to solve a basic problem in distributed statistical ...

Meimei Liu, et al. ∙

research

∙ 07/12/2018

A likelihood-ratio type test for stochastic block models with bounded degrees

A fundamental problem in network data analysis is to test Erdös-Rényi mo...

Mingao Yuan, et al. ∙

research

∙ 08/27/2018

Generalized Capsule Networks with Trainable Routing Procedure

CapsNet (Capsule Network) was first proposed by capsule and later anothe...

Zhenhua Chen, et al. ∙

research

∙ 08/24/2018

Code Generation for Higher Inductive Types

Higher inductive types are inductive types that include nontrivial highe...

Paventhan Vivekanandan, et al. ∙

research

∙ 09/08/2018

Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data

Detecting anomalous activity in human mobility data has a number of appl...

Kathryn Gray, et al. ∙

research

∙ 10/20/2018

MinJoin: Efficient Edit Similarity Joins via Local Hash Minimums

In this paper we study edit similarity joins, in which we are given a se...

Haoyu Zhang, et al. ∙

research

∙ 10/29/2018

Distinct Sampling on Streaming Data with Near-Duplicates

In this paper we study how to perform distinct sampling in the streaming...

Jiecao Chen, et al. ∙

research

∙ 11/20/2018

Community Organizations: Changing the Culture in Which Research Software Is Developed and Sustained

Software is the key crosscutting technology that enables advances in mat...

Daniel S Katz, et al. ∙

research

∙ 12/14/2018

Recycled Least Squares Estimation in Nonlinear Regression

We consider a resampling scheme for parameters estimates in nonlinear re...

Ben Boukai, et al. ∙

research

∙ 01/03/2019

Reachability and Differential based Heuristics for Solving Markov Decision Processes

The solution convergence of Markov Decision Processes (MDPs) can be acce...

Shoubhik Debnath, et al. ∙

research

∙ 01/24/2019

Optimal Nonparametric Inference under Quantization

Statistical inference based on lossy or incomplete samples is of fundame...

Ruiqi Liu, et al. ∙

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