
An efficient iterative method for reconstructing surface from point clouds
Surface reconstruction from point clouds is a fundamental step in many a...
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Equalizing Recourse across Groups
The rise in machine learningassisted decisionmaking has led to concern...
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Fair clustering via equitable group representations
What does it mean for a clustering to be fair? One popular approach seek...
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Problems with Shapleyvaluebased explanations as feature importance measures
Gametheoretic formulations of feature importance have become popular as...
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Feature Detection and Attenuation in Embeddings
Embedding is one of the fundamental building blocks for data analysis ta...
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Smoothed Analysis in Unsupervised Learning via Decoupling
Smoothed analysis is a powerful paradigm in overcoming worstcase intrac...
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Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest xrays
Knowledge of what spatial elements of medical images deep learning metho...
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dpVAEs: Fixing Sample Generation for Regularized VAEs
Unsupervised representation learning via generative modeling is a staple...
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A Fast Algorithm for Geodesic Active Contours with Applications to Medical Image Segmentation
The geodesic active contour model (GAC) is a commonly used segmentation ...
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Disentangling Influence: Using Disentangled Representations to Audit Model Predictions
Motivated by the need to audit complex and black box models, there has b...
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Simultaneous Edge Alignment and Learning
Edge detection is among the most fundamental vision problems for its rol...
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Novel Single View Constraints for Manhattan 3D Line Reconstruction
This paper proposes a novel and exact method to reconstruct linebased 3...
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Learning to Manipulate Object Collections Using Grounded State Representations
We propose a method for simtoreal robot learning which exploits simula...
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A Deterministic Streaming Sketch for Ridge Regression
We provide a deterministic spaceefficient algorithm for estimating ridg...
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INFOTABS: Inference on Tables as Semistructured Data
In this paper, we observe that semistructured tabulated text is ubiquit...
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CoopSubNet: Cooperating Subnetwork for DataDriven Regularization of Deep Networks under Limited Training Budgets
Deep networks are an integral part of the current machine learning parad...
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SetGANs: Enforcing Distributional Accuracy in Generative Adversarial Networks
This paper addresses the ability of generative adversarial networks (GAN...
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A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs
Tensor computations present significant performance challenges that impa...
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Optimizing Abstract Abstract Machines
The technique of abstracting abstract machines (AAM) provides a systemat...
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Learning Compact Recurrent Neural Networks with BlockTerm Tensor Decomposition
Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. H...
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The Riemannian Geometry of Deep Generative Models
Deep generative models learn a mapping from a low dimensional latent spa...
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Sparsely Connected and Disjointly Trained Deep Neural Networks for Low Resource Behavioral Annotation: Acoustic Classification in Couples' Therapy
Observational studies are based on accurate assessment of human state. A...
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Semisupervised Learning with GANs: Manifold Invariance with Improved Inference
Semisupervised learning methods using Generative Adversarial Networks (...
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Appearance invariance in convolutional networks with neighborhood similarity
We present a neighborhood similarity layer (NSL) which induces appearanc...
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Fair Pipelines
This work facilitates ensuring fairness of machine learning in the real ...
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Runaway Feedback Loops in Predictive Policing
Predictive policing systems are increasingly used to determine how to al...
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A Group Theoretic Perspective on Unsupervised Deep Learning
Why does Deep Learning work? What representations does it capture? How d...
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Disjunctive Normal Networks
Artificial neural networks are powerful pattern classifiers; however, th...
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Why does Deep Learning work?  A perspective from Group Theory
Why does Deep Learning work? What representations does it capture? How d...
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CASENet: Deep CategoryAware Semantic Edge Detection
Boundary and edge cues are highly beneficial in improving a wide variety...
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On the (im)possibility of fairness
What does it mean for an algorithm to be fair? Different papers use diff...
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The Robustness of Estimator Composition
We formalize notions of robustness for composite estimators via the noti...
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Auditing Blackbox Models for Indirect Influence
Datatrained predictive models see widespread use, but for the most part...
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MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors
Segmenting images of low quality or with missing data is a challenging p...
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Streaming Kernel Principal Component Analysis
Kernel principal component analysis (KPCA) provides a concise set of bas...
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IllinoisSL: A JAVA Library for Structured Prediction
IllinoisSL is a Java library for learning structured prediction models. ...
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SSHMT: Semisupervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation
Regionbased methods have proven necessary for improving segmentation ac...
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Regularization With Stochastic Transformations and Perturbations for Deep SemiSupervised Learning
Effective convolutional neural networks are trained on large sets of lab...
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Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs
Crowdsourcing platforms are now extensively used for conducting subjecti...
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Optimal Data Collection For Informative Rankings Expose WellConnected Graphs
Given a graph where vertices represent alternatives and arcs represent p...
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A Geometric Algorithm for Scalable Multiple Kernel Learning
We present a geometric formulation of the Multiple Kernel Learning (MKL)...
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Scene Labeling with Contextual Hierarchical Models
Scene labeling is the problem of assigning an object label to each pixel...
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Polynomial Regression on Riemannian Manifolds
In this paper we develop the theory of parametric polynomial regression ...
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Exploration of Heterogeneous Data Using Robust Similarity
Heterogeneous data pose serious challenges to data analysis tasks, inclu...
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Visual Detection of Structural Changes in TimeVarying Graphs Using Persistent Homology
Topological data analysis is an emerging area in exploratory data analys...
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Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue
The use of irony and sarcasm in social media allows us to study them at ...
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Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog
Effective models of social dialog must understand a broad range of rheto...
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And That's A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue
We investigate the characteristics of factual and emotional argumentatio...
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An Interactive Tool for Natural Language Processing on Clinical Text
Natural Language Processing (NLP) systems often make use of machine lear...
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Coping with Construals in BroadCoverage Semantic Annotation of Adpositions
We consider the semantics of prepositions, revisiting a broadcoverage a...
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