
Hypergraph Clustering: A Modularity Maximization Approach
Clustering on hypergraphs has been garnering increased attention with po...
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A Genetic Algorithm based Kernelsize Selection Approach for a Multicolumn Convolutional Neural Network
Deep neural networkbased architectures give promising results in variou...
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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...
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MTLE: A Multitask Learning Encoder of Visual Feature Representations for Video and Movie Description
Learning visual feature representations for video analysis is a daunting...
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HARE: a Flexible Highlighting Annotator for Ranking and Exploration
Exploration and analysis of potential data sources is a significant chal...
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Fast 3D Line Segment Detection From Unorganized Point Cloud
This paper presents a very simple but efficient algorithm for 3D line se...
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Freebreathing Cardiovascular MRI Using a PlugandPlay Method with Learned Denoiser
Cardiac magnetic resonance imaging (CMR) is a noninvasive imaging modali...
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Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning
This paper presents a novel modelfree reinforcement learning (RL) frame...
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SpiderBoost: A Class of Faster Variancereduced Algorithms for Nonconvex Optimization
There has been extensive research on developing stochastic variance redu...
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Private Stochastic Convex Optimization with Optimal Rates
We study differentially private (DP) algorithms for stochastic convex op...
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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...
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Two models of double descent for weak features
The "double descent" risk curve was recently proposed to qualitatively d...
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Cubic Regularization with Momentum for Nonconvex Optimization
Momentum is a popular technique to accelerate the convergence in practic...
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The UAVid Dataset for Video Semantic Segmentation
Video semantic segmentation has been one of the research focus in comput...
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MaSS: an Accelerated Stochastic Method for Overparametrized Learning
In this paper we introduce MaSS (Momentumadded Stochastic Solver), an a...
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Kernel Machines Beat Deep Neural Networks on Maskbased Singlechannel Speech Enhancement
We apply a fast kernel method for maskbased singlechannel speech enhan...
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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...
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Solver Recommendation For Transport Problems in Slabs Using Machine Learning
The use of machine learning algorithms to address classification problem...
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Convergence of Cubic Regularization for Nonconvex Optimization under KL Property
Cubicregularized Newton's method (CR) is a popular algorithm that guara...
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Topview Trajectories: A Pedestrian Dataset of VehicleCrowd Interaction from Controlled Experiments and Crowded Campus
Predicting the collective motion of a group of pedestrians (a crowd) und...
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A survey of statistical learning techniques as applied to inexpensive pediatric Obstructive Sleep Apnea data
Pediatric obstructive sleep apnea affects an estimated 15 elementarysc...
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Multimodal Content Analysis for Effective Advertisements on YouTube
The rapid advances in ecommerce and Web 2.0 technologies have greatly i...
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A ChangeDetection based Framework for Piecewisestationary MultiArmed Bandit Problem
The multiarmed bandit problem has been extensively studied under the st...
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Information Directed Sampling for Stochastic Bandits with Graph Feedback
We consider stochastic multiarmed bandit problems with graph feedback, ...
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Adaptive Bayesian Sampling with Monte Carlo EM
We present a novel technique for learning the mass matrices in samplers ...
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Learners that Leak Little Information
We study learning algorithms that are restricted to revealing little inf...
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Characterizing Driving Context from Driver Behavior
Because of the increasing availability of spatiotemporal data, a variety...
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Machine vs Machine: MinimaxOptimal Defense Against Adversarial Examples
Recently, researchers have discovered that the stateoftheart object c...
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Critical Points of Neural Networks: Analytical Forms and Landscape Properties
Due to the success of deep learning to solving a variety of challenging ...
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Nonconvex LowRank Matrix Recovery with Arbitrary Outliers via MedianTruncated Gradient Descent
Recent work has demonstrated the effectiveness of gradient descent for d...
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SecondOrder Word Embeddings from Nearest Neighbor Topological Features
We introduce secondorder vector representations of words, induced from ...
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Fast Change Point Detection on Dynamic Social Networks
A number of real world problems in many domains (e.g. sociology, biology...
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Unperturbed: spectral analysis beyond DavisKahan
Classical matrix perturbation results, such as Weyl's theorem for eigenv...
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Reward Maximization Under Uncertainty: Leveraging SideObservations on Networks
We study the stochastic multiarmed bandit (MAB) problem in the presence...
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Consistency of community detection in multilayer networks using spectral and matrix factorization methods
We consider the problem of estimating a consensus community structure by...
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Using Global Constraints and Reranking to Improve Cognates Detection
Global constraints and reranking have not been used in cognates detectio...
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Accelerated Stochastic QuasiNewton Optimization on Riemann Manifolds
We propose an LBFGS optimization algorithm on Riemannian manifolds usin...
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A GAMP Based Low Complexity Sparse Bayesian Learning Algorithm
In this paper, we present an algorithm for the sparse signal recovery pr...
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HeavyTailed Analogues of the Covariance Matrix for ICA
Independent Component Analysis (ICA) is the problem of learning a square...
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4d isip: 4d implicit surface interest point detection
In this paper, we propose a new method to detect 4D spatiotemporal inter...
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Admissible Hierarchical Clustering Methods and Algorithms for Asymmetric Networks
This paper characterizes hierarchical clustering methods that abide by t...
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Hierarchical Clustering of Asymmetric Networks
This paper considers networks where relationships between nodes are repr...
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Onsagercorrected deep learning for sparse linear inverse problems
Deep learning has gained great popularity due to its widespread success ...
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Graphons, mergeons, and so on!
In this work we develop a theory of hierarchical clustering for graphs. ...
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Reshaped Wirtinger Flow and Incremental Algorithm for Solving Quadratic System of Equations
We study the phase retrieval problem, which solves quadratic system of e...
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Generalized Sparse Precision Matrix Selection for Fitting Multivariate Gaussian Random Fields to Large Data Sets
We present a new method for estimating multivariate, secondorder statio...
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Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks
We propose a framework for inferring the latent attitudes or preferences...
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Gamma Processes, StickBreaking, and Variational Inference
While most Bayesian nonparametric models in machine learning have focuse...
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Combinatorial Topic Models using SmallVariance Asymptotics
Topic models have emerged as fundamental tools in unsupervised machine l...
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Learning and Free Energies for Vector Approximate Message Passing
Vector approximate message passing (VAMP) is a computationally simple ap...
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The Ohio State University
The Ohio State University, commonly referred to as Ohio State or OSU, is a large, primarily residential, public research university in Columbus, Ohio.