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Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?
Multiple fairness constraints have been proposed in the literature, moti...
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Deformable Style Transfer
Both geometry and texture are fundamental aspects of visual style. Exist...
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Style Transfer by Relaxed Optimal Transport and Self-Similarity
Style transfer algorithms strive to render the content of one image usin...
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ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Increasing model size when pretraining natural language representations ...
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Fingerspelling recognition in the wild with iterative visual attention
Sign language recognition is a challenging gesture sequence recognition ...
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Pixel Consensus Voting for Panoptic Segmentation
The core of our approach, Pixel Consensus Voting, is a framework for ins...
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Growing Efficient Deep Networks by Structured Continuous Sparsification
We develop an approach to training deep networks while dynamically adjus...
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Deep Anomaly Detection with Outlier Exposure
It is important to detect and handle anomalous inputs when deploying mac...
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Benchmarking Approximate Inference Methods for Neural Structured Prediction
Exact structured inference with neural network scoring functions is comp...
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Natural Adversarial Examples
We introduce natural adversarial examples -- real-world, unmodified, and...
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Domain-independent Dominance of Adaptive Methods
From a simplified analysis of adaptive methods, we derive AvaGrad, a new...
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Is Local SGD Better than Minibatch SGD?
We study local SGD (also known as parallel SGD and federated averaging),...
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Recurrent Back-Projection Network for Video Super-Resolution
We proposed a novel architecture for the problem of video super-resoluti...
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Generating Diverse Story Continuations with Controllable Semantics
We propose a simple and effective modeling framework for controlled gene...
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Task-Driven Super Resolution: Object Detection in Low-resolution Images
We consider how image super resolution (SR) can contribute to an object ...
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Towards Understanding the Role of Over-Parametrization in Generalization of Neural Networks
Despite existing work on ensuring generalization of neural networks in t...
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End-to-End Content and Plan Selection for Data-to-Text Generation
Learning to generate fluent natural language from structured data with n...
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Visually Grounded Neural Syntax Acquisition
We present the Visually Grounded Neural Syntax Learner (VG-NSL), an appr...
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Advancing subgroup fairness via sleeping experts
We study methods for improving fairness to subgroups in settings with ov...
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The Strategic Perceptron
The classical Perceptron algorithm provides a simple and elegant procedu...
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Multilingual Speech Recognition With A Single End-To-End Model
Training a conventional automatic speech recognition (ASR) system to sup...
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From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets
We propose a Las Vegas transformation of Markov Chain Monte Carlo (MCMC)...
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Active Tolerant Testing
In this work, we give the first algorithms for tolerant testing of nontr...
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Multigrid Neural Architectures
We propose a multigrid extension of convolutional neural networks (CNNs)...
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A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
We consider the two related problems of detecting if an example is miscl...
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Multitask training with unlabeled data for end-to-end sign language fingerspelling recognition
We address the problem of automatic American Sign Language fingerspellin...
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Multiplicative LSTM for sequence modelling
We introduce multiplicative LSTM (mLSTM), a recurrent neural network arc...
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Semantic keyword spotting by learning from images and speech
We consider the problem of representing semantic concepts in speech by l...
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Early Methods for Detecting Adversarial Images
Many machine learning classifiers are vulnerable to adversarial perturba...
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Adjusting for Dropout Variance in Batch Normalization and Weight Initialization
We show how to adjust for the variance introduced by dropout with correc...
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Sequence Training and Adaptation of Highway Deep Neural Networks
Highway deep neural network (HDNN) is a type of depth-gated feedforward ...
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Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation
We study the problem of recognition of fingerspelled letter sequences in...
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Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding
Spectral embedding provides a framework for solving perceptual organizat...
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Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition
End-to-end training of deep learning-based models allows for implicit le...
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Acoustic Feature Learning via Deep Variational Canonical Correlation Analysis
We study the problem of acoustic feature learning in the setting where w...
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Training Deep Networks to be Spatially Sensitive
In many computer vision tasks, for example saliency prediction or semant...
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Implicit Regularization in Matrix Factorization
We study implicit regularization when optimizing an underdetermined quad...
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Norm-Based Capacity Control in Neural Networks
We investigate the capacity, convexity and characterization of a general...
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Coherent Dialogue with Attention-based Language Models
We model coherent conversation continuation via RNN-based dialogue model...
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Jointly Learning to Align and Convert Graphemes to Phonemes with Neural Attention Models
We propose an attention-enabled encoder-decoder model for the problem of...
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Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation
Modern robotics applications that involve human-robot interaction requir...
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Stochastic Canonical Correlation Analysis
We tightly analyze the sample complexity of CCA, provide a learning algo...
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Stabilizing GAN Training with Multiple Random Projections
Training generative adversarial networks is unstable in high-dimensions ...
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Corralling a Band of Bandit Algorithms
We study the problem of combining multiple bandit algorithms (that is, o...
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Satellite Image-based Localization via Learned Embeddings
We propose a vision-based method that localizes a ground vehicle using p...
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Visually grounded learning of keyword prediction from untranscribed speech
During language acquisition, infants have the benefit of visual cues to ...
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End-to-End Training Approaches for Discriminative Segmental Models
Recent work on discriminative segmental models has shown that they can a...
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Single Pass PCA of Matrix Products
In this paper we present a new algorithm for computing a low rank approx...
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Colorization as a Proxy Task for Visual Understanding
We investigate and improve self-supervision as a drop-in replacement for...
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Comprehension-guided referring expressions
We consider generation and comprehension of natural language referring e...
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