The Ohio State University

research

∙ 05/02/2020

An Information-theoretic Visual Analysis Framework for Convolutional Neural Networks

Despite the great success of Convolutional Neural Networks (CNNs) in Com...

Jingyi Shen, et al. ∙

research

∙ 12/28/2018

Hypergraph Clustering: A Modularity Maximization Approach

Clustering on hypergraphs has been garnering increased attention with po...

Tarun Kumar, et al. ∙

research

∙ 12/28/2019

A Genetic Algorithm based Kernel-size Selection Approach for a Multi-column Convolutional Neural Network

Deep neural network-based architectures give promising results in variou...

Animesh Singh, et al. ∙

research

∙ 10/19/2020

Brain Atlas Guided Attention U-Net for White Matter Hyperintensity Segmentation

White Matter Hyperintensities (WMH) are the most common manifestation of...

Zicong Zhang, et al. ∙

research

∙ 09/15/2019

Road Network Reconstruction from Satellite Images with Machine Learning Supported by Topological Methods

Automatic Extraction of road network from satellite images is a goal tha...

Tamal K. Dey, et al. ∙

research

∙ 12/14/2021

TopNet: Learning from Neural Topic Model to Generate Long Stories

Long story generation (LSG) is one of the coveted goals in natural langu...

Yazheng Yang, et al. ∙

research

∙ 09/19/2018

MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description

Learning visual feature representations for video analysis is a daunting...

Oliver Nina, et al. ∙

research

∙ 05/17/2020

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

In the domain of autonomous driving, deep learning has substantially imp...

Yan Wang, et al. ∙

research

∙ 08/29/2019

HARE: a Flexible Highlighting Annotator for Ranking and Exploration

Exploration and analysis of potential data sources is a significant chal...

Denis Newman-Griffis, et al. ∙

research

∙ 07/02/2020

Posterior Model Adaptation With Updated Priors

Classification approaches based on the direct estimation and analysis of...

Jim Davis, et al. ∙

research

∙ 01/08/2019

Fast 3D Line Segment Detection From Unorganized Point Cloud

This paper presents a very simple but efficient algorithm for 3D line se...

Xiaohu Lu, et al. ∙

research

∙ 05/02/2020

An Imitation Game for Learning Semantic Parsers from User Interaction

Despite the widely successful applications, bootstrapping and fine-tunin...

Ziyu Yao, et al. ∙

research

∙ 05/21/2022

MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest

Graph Convolutional Networks (GCN) can efficiently integrate graph struc...

Saket Gurukar, et al. ∙

research

∙ 02/08/2020

Free-breathing Cardiovascular MRI Using a Plug-and-Play Method with Learned Denoiser

Cardiac magnetic resonance imaging (CMR) is a noninvasive imaging modali...

Sizhuo Liu, et al. ∙

research

∙ 10/03/2019

Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning

This paper presents a novel model-free reinforcement learning (RL) frame...

Guillermo A. Castillo, et al. ∙

research

∙ 10/25/2018

SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization

There has been extensive research on developing stochastic variance redu...

Zhe Wang, et al. ∙

research

∙ 08/27/2019

Private Stochastic Convex Optimization with Optimal Rates

We study differentially private (DP) algorithms for stochastic convex op...

Raef Bassily, et al. ∙

research

∙ 10/05/2021

Semi-Supervised Deep Learning for Multiplex Networks

Multiplex networks are complex graph structures in which a set of entiti...

Anasua Mitra, et al. ∙

research

∙ 06/13/2018

Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate

Many modern machine learning models are trained to achieve zero or near-...

Mikhail Belkin, et al. ∙

research

∙ 06/24/2020

Befriending The Byzantines Through Reputation Scores

We propose two novel stochastic gradient descent algorithms, ByGARS and ...

Jayanth Regatti, et al. ∙

research

∙ 07/25/2020

A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19

The outbreak of the novel coronavirus (COVID-19) is unfolding as a major...

Rahul Singh, et al. ∙

research

∙ 02/18/2022

GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations

We propose GNN-Surrogate, a graph neural network-based surrogate model t...

Neng Shi, et al. ∙

research

∙ 03/28/2022

Neural Vocoder is All You Need for Speech Super-resolution

Speech super-resolution (SR) is a task to increase speech sampling rate ...

Haohe Liu, et al. ∙

research

∙ 03/18/2019

Two models of double descent for weak features

The "double descent" risk curve was recently proposed to qualitatively d...

Mikhail Belkin, et al. ∙

research

∙ 04/07/2020

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection

Reliable and accurate 3D object detection is a necessity for safe autono...

Rui Qian, et al. ∙

research

∙ 04/08/2020

Understanding Knowledge Gaps in Visual Question Answering: Implications for Gap Identification and Testing

Visual Question Answering (VQA) systems are tasked with answering natura...

Goonmeet Bajaj, 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

∙ 09/27/2021

Mitigating Racial Biases in Toxic Language Detection with an Equity-Based Ensemble Framework

Recent research has demonstrated how racial biases against users who wri...

Matan Halevy, et al. ∙

research

∙ 10/09/2018

Cubic Regularization with Momentum for Nonconvex Optimization

Momentum is a popular technique to accelerate the convergence in practic...

Zhe Wang, et al. ∙

research

∙ 10/24/2018

The UAVid Dataset for Video Semantic Segmentation

Video semantic segmentation has been one of the research focus in comput...

Ye Lyu, et al. ∙

research

∙ 10/31/2018

MaSS: an Accelerated Stochastic Method for Over-parametrized Learning

In this paper we introduce MaSS (Momentum-added Stochastic Solver), an a...

Chaoyue Liu, et al. ∙

research

∙ 11/06/2018

Kernel Machines Beat Deep Neural Networks on Mask-based Single-channel Speech Enhancement

We apply a fast kernel method for mask-based single-channel speech enhan...

Like Hui, et al. ∙

research

∙ 07/08/2019

Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach

Travel time estimation is a crucial task for not only personal travel sc...

Wuwei Lan, et al. ∙

research

∙ 09/24/2021

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans

Accurately segmenting teeth and identifying the corresponding anatomical...

Tai-Hsien Wu, et al. ∙

research

∙ 06/19/2019

Solver Recommendation For Transport Problems in Slabs Using Machine Learning

The use of machine learning algorithms to address classification problem...

Jinzhao Chen, et al. ∙

research

∙ 04/22/2020

Logical Natural Language Generation from Open-Domain Tables

Neural natural language generation (NLG) models have recently shown rema...

Wenhu Chen, et al. ∙

research

∙ 04/27/2020

A Skip-connected Multi-column Network for Isolated Handwritten Bangla Character and Digit recognition

Finding local invariant patterns in handwrit-ten characters and/or digit...

Animesh Singh, et al. ∙

research

∙ 08/22/2018

Convergence of Cubic Regularization for Nonconvex Optimization under KL Property

Cubic-regularized Newton's method (CR) is a popular algorithm that guara...

Yi Zhou, et al. ∙

research

∙ 02/01/2019

Top-view Trajectories: A Pedestrian Dataset of Vehicle-Crowd Interaction from Controlled Experiments and Crowded Campus

Predicting the collective motion of a group of pedestrians (a crowd) und...

Dongfang Yang, et al. ∙

research

∙ 06/06/2020

Contextual Bandits with Side-Observations

We investigate contextual bandits in the presence of side-observations a...

Rahul Singh, et al. ∙

research

∙ 09/29/2021

Temporal Clustering with External Memory Network for Disease Progression Modeling

Disease progression modeling (DPM) involves using mathematical framework...

Zicong Zhang, et al. ∙

research

∙ 05/19/2022

Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes

Despite intense efforts in basic and clinical research, an individualize...

Changchang Yin, et al. ∙

research

∙ 07/21/2016

Hierarchical Clustering of Asymmetric Networks

This paper considers networks where relationships between nodes are repr...

Gunnar Carlsson, et al. ∙

research

∙ 02/17/2020

A survey of statistical learning techniques as applied to inexpensive pediatric Obstructive Sleep Apnea data

Pediatric obstructive sleep apnea affects an estimated 1-5 elementary-sc...

Emily T. Winn, et al. ∙

research

∙ 05/24/2022

Learning to Drive Using Sparse Imitation Reinforcement Learning

In this paper, we propose Sparse Imitation Reinforcement Learning (SIRL)...

Yuci Han, et al. ∙

research

∙ 09/12/2017

Multimodal Content Analysis for Effective Advertisements on YouTube

The rapid advances in e-commerce and Web 2.0 technologies have greatly i...

Nikhita Vedula, et al. ∙

research

∙ 11/08/2017

A Change-Detection based Framework for Piecewise-stationary Multi-Armed Bandit Problem

The multi-armed bandit problem has been extensively studied under the st...

Fang Liu, et al. ∙

research

∙ 11/08/2017

Information Directed Sampling for Stochastic Bandits with Graph Feedback

We consider stochastic multi-armed bandit problems with graph feedback, ...

Fang Liu, et al. ∙

research

∙ 11/06/2017

Adaptive Bayesian Sampling with Monte Carlo EM

We present a novel technique for learning the mass matrices in samplers ...

Anirban Roychowdhury, et al. ∙

research

∙ 10/14/2017

Learners that Leak Little Information

We study learning algorithms that are restricted to revealing little inf...

Raef Bassily, et al. ∙

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