The Ohio State University

∙ Columbus , United States ∙ 0 followers

The Ohio State University, commonly referred to as Ohio State or OSU, is a large, primarily residential, public research university in Columbus, Ohio.

Hypergraph Clustering: A Modularity Maximization Approach

Clustering on hypergraphs has been garnering increased attention with po...
12/28/2018 ∙ by Tarun Kumar, et al. ∙ 28 ∙ share

read it
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...
12/28/2019 ∙ by Animesh Singh, et al. ∙ 27 ∙ share

read it
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...
09/15/2019 ∙ by Tamal K. Dey, et al. ∙ 21 ∙ share

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

Learning visual feature representations for video analysis is a daunting...
09/19/2018 ∙ by Oliver Nina, et al. ∙ 18 ∙ share

read it
HARE: a Flexible Highlighting Annotator for Ranking and Exploration

Exploration and analysis of potential data sources is a significant chal...
08/29/2019 ∙ by Denis Newman-Griffis, et al. ∙ 16 ∙ share

read it
Fast 3D Line Segment Detection From Unorganized Point Cloud

This paper presents a very simple but efficient algorithm for 3D line se...
01/08/2019 ∙ by Xiaohu Lu, et al. ∙ 14 ∙ share

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

Cardiac magnetic resonance imaging (CMR) is a noninvasive imaging modali...
02/08/2020 ∙ by Sizhuo Liu, et al. ∙ 12 ∙ share

read it
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...
10/03/2019 ∙ by Guillermo A. Castillo, et al. ∙ 10 ∙ share

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

There has been extensive research on developing stochastic variance redu...
10/25/2018 ∙ by Zhe Wang, et al. ∙ 9 ∙ share

read it
Private Stochastic Convex Optimization with Optimal Rates

We study differentially private (DP) algorithms for stochastic convex op...
08/27/2019 ∙ by Raef Bassily, et al. ∙ 9 ∙ share

read it
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-...
06/13/2018 ∙ by Mikhail Belkin, et al. ∙ 8 ∙ share

read it
Two models of double descent for weak features

The "double descent" risk curve was recently proposed to qualitatively d...
03/18/2019 ∙ by Mikhail Belkin, et al. ∙ 6 ∙ share

read it
Cubic Regularization with Momentum for Nonconvex Optimization

Momentum is a popular technique to accelerate the convergence in practic...
10/09/2018 ∙ by Zhe Wang, et al. ∙ 4 ∙ share

read it
The UAVid Dataset for Video Semantic Segmentation

Video semantic segmentation has been one of the research focus in comput...
10/24/2018 ∙ by Ye Lyu, et al. ∙ 4 ∙ share

read it
MaSS: an Accelerated Stochastic Method for Over-parametrized Learning

In this paper we introduce MaSS (Momentum-added Stochastic Solver), an a...
10/31/2018 ∙ by Chaoyue Liu, et al. ∙ 4 ∙ share

read it
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...
11/06/2018 ∙ by Like Hui, et al. ∙ 4 ∙ share

read it
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...
07/08/2019 ∙ by Wuwei Lan, et al. ∙ 4 ∙ share

read it
Solver Recommendation For Transport Problems in Slabs Using Machine Learning

The use of machine learning algorithms to address classification problem...
06/19/2019 ∙ by Jinzhao Chen, et al. ∙ 3 ∙ share

read it
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property

Cubic-regularized Newton's method (CR) is a popular algorithm that guara...
08/22/2018 ∙ by Yi Zhou, et al. ∙ 2 ∙ share

read it
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...
02/01/2019 ∙ by Dongfang Yang, et al. ∙ 2 ∙ share

read it
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...
02/17/2020 ∙ by Emily T. Winn, et al. ∙ 1 ∙ share

read it
Multimodal Content Analysis for Effective Advertisements on YouTube

The rapid advances in e-commerce and Web 2.0 technologies have greatly i...
09/12/2017 ∙ by Nikhita Vedula, et al. ∙ 0 ∙ share

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

The multi-armed bandit problem has been extensively studied under the st...
11/08/2017 ∙ by Fang Liu, et al. ∙ 0 ∙ share

read it
Information Directed Sampling for Stochastic Bandits with Graph Feedback

We consider stochastic multi-armed bandit problems with graph feedback, ...
11/08/2017 ∙ by Fang Liu, et al. ∙ 0 ∙ share

read it
Adaptive Bayesian Sampling with Monte Carlo EM

We present a novel technique for learning the mass matrices in samplers ...
11/06/2017 ∙ by Anirban Roychowdhury, et al. ∙ 0 ∙ share

read it
Learners that Leak Little Information

We study learning algorithms that are restricted to revealing little inf...
10/14/2017 ∙ by Raef Bassily, et al. ∙ 0 ∙ share

read it
Characterizing Driving Context from Driver Behavior

Because of the increasing availability of spatiotemporal data, a variety...
10/13/2017 ∙ by Sobhan Moosavi, et al. ∙ 0 ∙ share

read it
Machine vs Machine: Minimax-Optimal Defense Against Adversarial Examples

Recently, researchers have discovered that the state-of-the-art object c...
11/12/2017 ∙ by Jihun Hamm, et al. ∙ 0 ∙ share

read it
Critical Points of Neural Networks: Analytical Forms and Landscape Properties

Due to the success of deep learning to solving a variety of challenging ...
10/30/2017 ∙ by Yi Zhou, et al. ∙ 0 ∙ share

read it
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent

Recent work has demonstrated the effectiveness of gradient descent for d...
09/23/2017 ∙ by Yuanxin Li, et al. ∙ 0 ∙ share

read it
Second-Order Word Embeddings from Nearest Neighbor Topological Features

We introduce second-order vector representations of words, induced from ...
05/23/2017 ∙ by Denis Newman-Griffis, et al. ∙ 0 ∙ share

read it
Fast Change Point Detection on Dynamic Social Networks

A number of real world problems in many domains (e.g. sociology, biology...
05/20/2017 ∙ by Yu Wang, et al. ∙ 0 ∙ share

read it
Unperturbed: spectral analysis beyond Davis-Kahan

Classical matrix perturbation results, such as Weyl's theorem for eigenv...
06/20/2017 ∙ by Justin Eldridge, et al. ∙ 0 ∙ share

read it
Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks

We study the stochastic multi-armed bandit (MAB) problem in the presence...
04/26/2017 ∙ by Swapna Buccapatnam, et al. ∙ 0 ∙ share

read it
Consistency of community detection in multi-layer networks using spectral and matrix factorization methods

We consider the problem of estimating a consensus community structure by...
04/24/2017 ∙ by Subhadeep Paul, et al. ∙ 0 ∙ share

read it
Using Global Constraints and Reranking to Improve Cognates Detection

Global constraints and reranking have not been used in cognates detectio...
04/24/2017 ∙ by Michael Bloodgood, et al. ∙ 0 ∙ share

read it
Accelerated Stochastic Quasi-Newton Optimization on Riemann Manifolds

We propose an L-BFGS optimization algorithm on Riemannian manifolds usin...
04/06/2017 ∙ by Anirban Roychowdhury, et al. ∙ 0 ∙ share

read it
A GAMP Based Low Complexity Sparse Bayesian Learning Algorithm

In this paper, we present an algorithm for the sparse signal recovery pr...
03/08/2017 ∙ by Maher Al-Shoukairi, et al. ∙ 0 ∙ share

read it
Heavy-Tailed Analogues of the Covariance Matrix for ICA

Independent Component Analysis (ICA) is the problem of learning a square...
02/22/2017 ∙ by Joseph Anderson, et al. ∙ 0 ∙ share

read it
4d isip: 4d implicit surface interest point detection

In this paper, we propose a new method to detect 4D spatiotemporal inter...
05/10/2017 ∙ by Shirui Li, et al. ∙ 0 ∙ share

read it
Admissible Hierarchical Clustering Methods and Algorithms for Asymmetric Networks

This paper characterizes hierarchical clustering methods that abide by t...
07/21/2016 ∙ by Gunnar Carlsson, et al. ∙ 0 ∙ share

read it
Hierarchical Clustering of Asymmetric Networks

This paper considers networks where relationships between nodes are repr...
07/21/2016 ∙ by Gunnar Carlsson, et al. ∙ 0 ∙ share

read it
Onsager-corrected deep learning for sparse linear inverse problems

Deep learning has gained great popularity due to its widespread success ...
07/20/2016 ∙ by Mark Borgerding, et al. ∙ 0 ∙ share

read it
Graphons, mergeons, and so on!

In this work we develop a theory of hierarchical clustering for graphs. ...
07/06/2016 ∙ by Justin Eldridge, et al. ∙ 0 ∙ share

read it
Reshaped Wirtinger Flow and Incremental Algorithm for Solving Quadratic System of Equations

We study the phase retrieval problem, which solves quadratic system of e...
05/25/2016 ∙ by Huishuai Zhang, et al. ∙ 0 ∙ share

read it
Generalized Sparse Precision Matrix Selection for Fitting Multivariate Gaussian Random Fields to Large Data Sets

We present a new method for estimating multivariate, second-order statio...
05/11/2016 ∙ by Sam Davanloo Tajbakhsh, et al. ∙ 0 ∙ share

read it
Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks

We propose a framework for inferring the latent attitudes or preferences...
11/11/2014 ∙ by Jiwei Li, et al. ∙ 0 ∙ share

read it
Gamma Processes, Stick-Breaking, and Variational Inference

While most Bayesian nonparametric models in machine learning have focuse...
10/04/2014 ∙ by Anirban Roychowdhury, et al. ∙ 0 ∙ share

read it
Combinatorial Topic Models using Small-Variance Asymptotics

Topic models have emerged as fundamental tools in unsupervised machine l...
04/07/2016 ∙ by Ke Jiang, et al. ∙ 0 ∙ share

read it
Learning and Free Energies for Vector Approximate Message Passing

Vector approximate message passing (VAMP) is a computationally simple ap...
02/26/2016 ∙ by Alyson K. Fletcher, et al. ∙ 0 ∙ share

read it

The Ohio State University

Featured Researchers