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08/21/2023
CoNe: Contrast Your Neighbours for Supervised Image Classification
Image classification is a longstanding problem in computer vision and ma...
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08/13/2023
SimMatchV2: Semi-Supervised Learning with Graph Consistency
Semi-Supervised image classification is one of the most fundamental prob...
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07/25/2023
Re-mine, Learn and Reason: Exploring the Cross-modal Semantic Correlations for Language-guided HOI detection
Human-Object Interaction (HOI) detection is a challenging computer visio...
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04/21/2023
Can GPT-4 Perform Neural Architecture Search?
We investigate the potential of GPT-4~\cite{gpt4} to perform Neural Arch...
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10/26/2022
Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations
Recent breakthroughs in semi-supervised semantic segmentation have been ...
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07/15/2022
ScaleNet: Searching for the Model to Scale
Recently, community has paid increasing attention on model scaling and c...
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07/12/2022
LightViT: Towards Light-Weight Convolution-Free Vision Transformers
Vision transformers (ViTs) are usually considered to be less light-weigh...
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05/26/2022
Green Hierarchical Vision Transformer for Masked Image Modeling
We present an efficient approach for Masked Image Modeling (MIM) with hi...
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05/21/2022
Knowledge Distillation from A Stronger Teacher
Unlike existing knowledge distillation methods focus on the baseline set...
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04/30/2022
Taylor, Can You Hear Me Now? A Taylor-Unfolding Framework for Monaural Speech Enhancement
While the deep learning techniques promote the rapid development of the ...
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03/28/2022
Learning Where to Learn in Cross-View Self-Supervised Learning
Self-supervised learning (SSL) has made enormous progress and largely na...
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03/25/2022
Searching for Network Width with Bilaterally Coupled Network
Searching for a more compact network width recently serves as an effecti...
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03/24/2022
DyRep: Bootstrapping Training with Dynamic Re-parameterization
Structural re-parameterization (Rep) methods achieve noticeable improvem...
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03/16/2022
Relational Self-Supervised Learning
Self-supervised Learning (SSL) including the mainstream contrastive lear...
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03/14/2022
SimMatch: Semi-supervised Learning with Similarity Matching
Learning with few labeled data has been a longstanding problem in the co...
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02/26/2022
Relational Surrogate Loss Learning
Evaluation metrics in machine learning are often hardly taken as loss fu...
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11/24/2021
GreedyNASv2: Greedier Search with a Greedy Path Filter
Training a good supernet in one-shot NAS methods is difficult since the ...
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10/10/2021
Weakly Supervised Contrastive Learning
Unsupervised visual representation learning has gained much attention fr...
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07/20/2021
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
Self-supervised Learning (SSL) including the mainstream contrastive lear...
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06/25/2021
Vision Transformer Architecture Search
Recently, transformers have shown great superiority in solving computer ...
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06/11/2021
K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets
In one-shot weight sharing for NAS, the weights of each operation (at ea...
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05/21/2021
BCNet: Searching for Network Width with Bilaterally Coupled Network
Searching for a more compact network width recently serves as an effecti...
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03/22/2021
Prioritized Architecture Sampling with Monto-Carlo Tree Search
One-shot neural architecture search (NAS) methods significantly reduce t...
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02/10/2021
Locally Free Weight Sharing for Network Width Search
Searching for network width is an effective way to slim deep neural netw...
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01/27/2021
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search
Most differentiable neural architecture search methods construct a super...
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11/18/2020
Explicitly Learning Topology for Differentiable Neural Architecture Search
Differentiable neural architecture search (DARTS) has gained much succes...
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10/28/2020
Data Agnostic Filter Gating for Efficient Deep Networks
To deploy a well-trained CNN model on low-end computation edge devices, ...
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10/20/2020
Quantum circuit architecture search: error mitigation and trainability enhancement for variational quantum solvers
Quantum error mitigation techniques are at the heart of quantum computat...
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10/13/2020
ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding
Neural architecture search (NAS) aims to produce the optimal sparse solu...
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07/23/2020
Quantum differentially private sparse regression learning
Differentially private (DP) learning, which aims to accurately extract p...
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03/25/2020
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet
Training a supernet matters for one-shot neural architecture search (NAS...
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07/13/2019
Bringing Giant Neural Networks Down to Earth with Unlabeled Data
Compressing giant neural networks has gained much attention for their ex...
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01/25/2017
Privileged Multi-label Learning
This paper presents privileged multi-label learning (PrML) to explore an...
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04/19/2016
Parts for the Whole: The DCT Norm for Extreme Visual Recovery
Here we study the extreme visual recovery problem, in which over 90% of ...
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04/19/2016
