
TorchStruct: Deep Structured Prediction Library
The literature on structured prediction for NLP describes a rich collect...
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ATGAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets
Recent studies have discovered the vulnerability of Deep Neural Networks...
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AutoML using Metadata Language Embeddings
As a human choosing a supervised learning algorithm, it is natural to be...
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Mixed Reinforcement Learning with Additive Stochastic Uncertainty
Reinforcement learning (RL) methods often rely on massive exploration da...
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Convolutional Networks with Dense Connectivity
Recent work has shown that convolutional networks can be substantially d...
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A Simple Baseline for Bayesian Uncertainty in Deep Learning
We propose SWAGaussian (SWAG), a simple, scalable, and general purpose ...
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PseudoLiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Detecting objects such as cars and pedestrians in 3D plays an indispensa...
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When Does Selfsupervision Improve Fewshot Learning?
We present a technique to improve the generalization of deep representat...
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Blameworthiness in MultiAgent Settings
We provide a formal definition of blameworthiness in settings where mult...
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CAB: Continuous Adaptive Blending Estimator for Policy Evaluation and Learning
The ability to perform offline A/Btesting and offpolicy learning using...
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PseudoLiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
3D object detection is an essential task in autonomous driving. Recent t...
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Confidence Calibration for Convolutional Neural Networks Using Structured Dropout
In classification applications, we often want probabilistic predictions ...
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Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
In this paper, we propose a fast surrogate leverage weighted sampling st...
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Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces
Classical deformable registration techniques achieve impressive results ...
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Efficient Rollout Strategies for Bayesian Optimization
Bayesian optimization (BO) is a class of sampleefficient global optimiz...
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Unsupervised Data Imputation via Variational Inference of Deep Subspaces
A wide range of systems exhibit high dimensional incomplete data. Accura...
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Robust Local Features for Improving the Generalization of Adversarial Training
Adversarial training has been demonstrated as one of the most effective ...
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Efficient Policy Learning from SurrogateLoss Classification Reductions
Recent work on policy learning from observational data has highlighted t...
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ContextualBandit Based Personalized Recommendation with TimeVarying User Interests
A contextual bandit problem is studied in a highly nonstationary enviro...
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Lowvolatility Anomaly and the Adaptive MultiFactor Model
The paper explains the lowvolatility anomaly from a new perspective. We...
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Low Frequency Adversarial Perturbation
Recently, machine learning security has received significant attention. ...
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Neural Naturalist: Generating FineGrained Image Comparisons
We introduce the new BirdstoWords dataset of 41k sentences describing ...
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Retouchdown: Adding Touchdown to StreetLearn as a Shareable Resource for Language Grounding Tasks in Street View
The Touchdown dataset (Chen et al., 2019) provides instructions by human...
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Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction
Identifying changes in model parameters is fundamental in machine learni...
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Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Recurrent Neural Networks (RNNs) and their variants, such as LongShort ...
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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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Fair LearningtoRank from Implicit Feedback
Addressing unfairness in rankings has become an increasingly important p...
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On the Distribution of Minima in IntrinsicMetric Rotation Averaging
Rotation Averaging is a nonconvex optimization problem that determines ...
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GeoStyle: Discovering Fashion Trends and Events
Understanding fashion styles and trends is of great potential interest t...
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Boosting Supervision with SelfSupervision for Fewshot Learning
We present a technique to improve the transferability of deep representa...
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Approximate Causal Abstraction
Scientific models describe natural phenomena at different levels of abst...
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Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation
We consider the problem of segmenting a biomedical image into anatomical...
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Positional Normalization
A widely deployed method for reducing the training time of deep neural n...
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Adversarially robust transfer learning
Transfer learning, in which a network is trained on one task and repurp...
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An Unsupervised Learning Model for Deformable Medical Image Registration
We present an efficient learningbased algorithm for deformable, pairwis...
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A Debiased MDI Feature Importance Measure for Random Forests
Tree ensembles such as Random Forests have achieved impressive empirical...
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A Conceptually WellFounded Characterization of Iterated Admissibility Using an "All I Know" Operator
Brandenburger, Friedenberg, and Keisler provide an epistemic characteriz...
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Recombinator Networks: Learning CoarsetoFine Feature Aggregation
Deep neural networks with alternating convolutional, maxpooling and dec...
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Asymmetric Minwise Hashing
Minwise hashing (Minhash) is a widely popular indexing scheme in practic...
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Compressed Counting
Counting is among the most fundamental operations in computing. For exam...
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Bayesian Qlearning with Assumed Density Filtering
While offpolicy temporal difference methods have been broadly used in r...
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Estimating the error variance in a highdimensional linear model
The lasso has been studied extensively as a tool for estimating the coef...
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DOTA: A Largescale Dataset for Object Detection in Aerial Images
Object detection is an important and challenging problem in computer vis...
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CondenseNet: An Efficient DenseNet using Learned Group Convolutions
Deep neural networks are increasingly used on mobile devices, where comp...
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Spectrallynormalized margin bounds for neural networks
This paper presents a marginbased multiclass generalization bound for n...
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Detecting Bias in BlackBox Models Using Transparent Model Distillation
Blackbox risk scoring models permeate our lives, yet are typically prop...
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Interpretable Vector AutoRegressions with Exogenous Time Series
The Vector AutoRegressive (VAR) model is fundamental to the study of mul...
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Traffic Optimization For a Mixture of Selfinterested and Compliant Agents
This paper focuses on two commonly used path assignment policies for age...
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Learning Compositional Visual Concepts with Mutual Consistency
Compositionality of semantic concepts in image synthesis and analysis is...
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The Local Dimension of Deep Manifold
Based on our observation that there exists a dramatic drop for the singu...
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