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12/09/2022
Object Goal Navigation with End-to-End Self-Supervision
A household robot should be able to navigate to target locations without...
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10/22/2022
Greedy Modality Selection via Approximate Submodular Maximization
Multimodal learning considers learning from multi-modality data, aiming ...
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09/27/2022
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents
The perception system in personalized mobile agents requires developing ...
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09/25/2022
Paraphrasing Is All You Need for Novel Object Captioning
Novel object captioning (NOC) aims to describe images containing objects...
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07/22/2022
Scale dependant layer for self-supervised nuclei encoding
Recent developments in self-supervised learning give us the possibility ...
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02/14/2022
Learning Weakly-Supervised Contrastive Representations
We argue that a form of the valuable information provided by the auxilia...
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02/11/2022
Conditional Contrastive Learning with Kernel
Conditional contrastive learning frameworks consider the conditional sam...
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06/14/2021
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
Self-supervised approaches for speech representation learning are challe...
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06/05/2021
Integrating Auxiliary Information in Self-supervised Learning
This paper presents to integrate the auxiliary information (e.g., additi...
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06/05/2021
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations
Self-supervised learning is a form of unsupervised learning that leverag...
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04/28/2021
A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning
In this report, we relate the algorithmic design of Barlow Twins' method...
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03/21/2021
Self-supervised Representation Learning with Relative Predictive Coding
This paper introduces Relative Predictive Coding (RPC), a new contrastiv...
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10/27/2020
Unsupervised Domain Adaptation for Visual Navigation
Advances in visual navigation methods have led to intelligent embodied n...
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06/10/2020
Demystifying Self-Supervised Learning: An Information-Theoretical Framework
Self-supervised representation learning adopts self-defined signals as s...
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06/09/2020
Neural Methods for Point-wise Dependency Estimation
Since its inception, the neural estimation of mutual information (MI) ha...
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05/25/2020
Feature Robust Optimal Transport for High-dimensional Data
Optimal transport is a machine learning technique with applications incl...
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04/29/2020
Interpretable Multimodal Routing for Human Multimodal Language
The human language has heterogeneous sources of information, including t...
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02/12/2020
Capsules with Inverted Dot-Product Attention Routing
We introduce a new routing algorithm for capsule networks, in which a ch...
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10/22/2019
Complex Transformer: A Framework for Modeling Complex-Valued Sequence
While deep learning has received a surge of interest in a variety of fie...
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09/05/2019
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport
Estimating mutual information is an important machine learning and stati...
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08/30/2019
Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel
Transformer is a powerful architecture that achieves superior performanc...
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07/14/2019
Learning Neural Networks with Adaptive Regularization
Feed-forward neural networks can be understood as a combination of an in...
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07/01/2019
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization
There has been an increased interest in multimodal language processing i...
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06/01/2019
Multimodal Transformer for Unaligned Multimodal Language Sequences
Human language is often multimodal, which comprehends a mixture of natur...
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05/14/2019
Strong and Simple Baselines for Multimodal Utterance Embeddings
Human language is a rich multimodal signal consisting of spoken words, f...
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03/25/2019
Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph
Visual relationship reasoning is a crucial yet challenging task for unde...
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06/16/2018
Learning Factorized Multimodal Representations
Learning representations of multimodal data is a fundamentally complex r...
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02/17/2018
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
Measuring divergence between two distributions is essential in machine l...
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02/15/2018
Selecting the Best in GANs Family: a Post Selection Inference Framework
"Which Generative Adversarial Networks (GANs) generates the most plausib...
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02/15/2018
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study
Recent works investigated the generalization properties in deep neural n...
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03/17/2017