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10/14/2022
Pareto-aware Neural Architecture Generation for Diverse Computational Budgets
Designing feasible and effective architectures under diverse computation...
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02/27/2021
Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets
Designing feasible and effective architectures under diverse computation...
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02/20/2021
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Designing effective architectures is one of the key factors behind the s...
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08/07/2020
A Surgery of the Neural Architecture Evaluators
Neural architecture search (NAS) recently received extensive attention d...
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04/04/2020
A Generic Graph-based Neural Architecture Encoding Scheme for Predictor-based NAS
This work proposes a novel Graph-based neural ArchiTecture Encoding Sche...
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03/20/2020
FTT-NAS: Discovering Fault-Tolerant Neural Architecture
With the fast evolvement of embedded deep-learning computing systems, ap...
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10/31/2019
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Designing effective architectures is one of the key factors behind the s...
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05/25/2019
Semi-supervised Learning with Contrastive Predicative Coding
Semi-supervised learning (SSL) provides a powerful framework for leverag...
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05/18/2019
RaFM: Rank-Aware Factorization Machines
Factorization machines (FM) are a popular model class to learn pairwise ...
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03/10/2019
Fast Single Image Reflection Suppression via Convex Optimization
Removing undesired reflections from images taken through the glass is of...
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06/18/2018
Nonparametric Topic Modeling with Neural Inference
This work focuses on combining nonparametric topic models with Auto-Enco...
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11/16/2016
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
Clustering is among the most fundamental tasks in computer vision and ma...
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05/31/2016
A Neural Autoregressive Approach to Collaborative Filtering
This paper proposes CF-NADE, a neural autoregressive architecture for co...
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03/18/2016
Document Neural Autoregressive Distribution Estimation
We present an approach based on feed-forward neural networks for learnin...
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11/24/2015
Dynamic Capacity Networks
We introduce the Dynamic Capacity Network (DCN), a neural network that c...
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09/13/2014
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data
Topic modeling based on latent Dirichlet allocation (LDA) has been a fra...
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05/23/2013