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Image Captioning as an Assistive Technology: Lessons Learned from VizWiz 2020 Challenge
Image captioning has recently demonstrated impressive progress largely o...
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Alleviating Noisy Data in Image Captioning with Cooperative Distillation
Image captioning systems have made substantial progress, largely due to ...
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On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
We consider the maximum mean discrepancy (MMD) GAN problem and propose a...
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Tabular Transformers for Modeling Multivariate Time Series
Tabular datasets are ubiquitous in data science applications. Given thei...
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Unbalanced Sobolev Descent
We introduce Unbalanced Sobolev Descent (USD), a particle descent algori...
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Active learning of deep surrogates for PDEs: Application to metasurface design
Surrogate models for partial-differential equations are widely used in t...
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Kernel Stein Generative Modeling
We are interested in gradient-based Explicit Generative Modeling where s...
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Fast Mixing of Multi-Scale Langevin Dynamics under the Manifold Hypothesis
Recently, the task of image generation has attracted much attention. In ...
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Fast Mixing of Multi-Scale Langevin Dynamics underthe Manifold Hypothesis
Recently, the task of image generation has attracted much attention. In ...
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Learning Implicit Text Generation via Feature Matching
Generative feature matching network (GFMN) is an approach for training i...
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Improving Efficiency in Large-Scale Decentralized Distributed Training
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
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Generative Modeling with Denoising Auto-Encoders and Langevin Sampling
We study convergence of a generative modeling method that first estimate...
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Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets
Adaptive gradient algorithms perform gradient-based updates using the hi...
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Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces
This paper focuses on the problem of unsupervised alignment of hierarchi...
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Sobolev Independence Criterion
We propose the Sobolev Independence Criterion (SIC), an interpretable de...
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Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Generative Adversarial Networks (GANs) are powerful class of generative ...
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Wasserstein Style Transfer
We propose Gaussian optimal transport for Image style transfer in an Enc...
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Learning Implicit Generative Models by Matching Perceptual Features
Perceptual features (PFs) have been used with great success in tasks suc...
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Implicit Kernel Learning
Kernels are powerful and versatile tools in machine learning and statist...
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Wasserstein Barycenter Model Ensembling
In this paper we propose to perform model ensembling in a multiclass or ...
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Regularized Kernel and Neural Sobolev Descent: Dynamic MMD Transport
We introduce Regularized Kernel and Neural Sobolev Descent for transport...
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Regularized Finite Dimensional Kernel Sobolev Discrepancy
We show in this note that the Sobolev Discrepancy introduced in Mroueh e...
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Improved Image Captioning with Adversarial Semantic Alignment
In this paper we propose a new conditional GAN for image captioning that...
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Semi-Supervised Learning with IPM-based GANs: an Empirical Study
We present an empirical investigation of a recent class of Generative Ad...
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Sobolev GAN
We propose a new Integral Probability Metric (IPM) between distributions...
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Fisher GAN
Generative Adversarial Networks (GANs) are powerful models for learning ...
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McGan: Mean and Covariance Feature Matching GAN
We introduce new families of Integral Probability Metrics (IPM) for trai...
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Self-critical Sequence Training for Image Captioning
Recently it has been shown that policy-gradient methods for reinforcemen...
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Random Maxout Features
In this paper, we propose and study random maxout features, which are co...
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Learning with Group Invariant Features: A Kernel Perspective
We analyze in this paper a random feature map based on a theory of invar...
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Deep Multimodal Learning for Audio-Visual Speech Recognition
In this paper, we present methods in deep multimodal learning for fusing...
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Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?
The standard approach to unconstrained face recognition in natural photo...
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Multiclass Learning with Simplex Coding
In this paper we discuss a novel framework for multiclass learning, defi...
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