Results 21 to 30 of about 3,080,648 (304)
Bayesian Optimization Meets Self-Distillation
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Bayesian optimization (BO) has contributed greatly to improving model performance by suggesting promising hyperparameter configurations iteratively based on observations from multiple training trials. However, only partial knowledge (i.e., the measured performances of trained models and their hyperparameter configurations) from previous trials is ...
HyunJae Lee +5 more
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Understanding the Gains from Repeated Self-Distillation
Advances in Neural Information Processing Systems 37Self-Distillation is a special type of knowledge distillation where the student model has the same architecture as the teacher model. Despite using the same architecture and the same training data, self-distillation has been empirically observed to improve performance, especially when applied repeatedly.
Divyansh Pareek, Simon S. Du, Sewoong Oh
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Domain-Agnostic Clustering with Self-Distillation
CoRR, 2021 NeurIPS 2021 Workshop: Self-Supervised Learning - Theory and ...
Mohammed Adnan +3 more
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Self-Learning for Few-Shot Remote Sensing Image Captioning
Remote Sensing, 2022 Large-scale caption-labeled remote sensing image samples are expensive to acquire, and the training samples available in practical application scenarios are generally limited.
Haonan Zhou +3 more
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Self-distillation for Surgical Action Recognition
, 2023 Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpassed human performance in various fields, the task of surgical action recognition remains a major challenge.
Amine Yamlahi +11 more
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A Lightweight Graph Neural Network Algorithm for Action Recognition Based on Self-Distillation
Algorithms, 2023 Recognizing human actions can help in numerous ways, such as health monitoring, intelligent surveillance, virtual reality and human–computer interaction. A quick and accurate detection algorithm is required for daily real-time detection. This paper first
Miao Feng, Jean Meunier
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SdAE: Self-distillated Masked Autoencoder
, 2022 With the development of generative-based self-supervised learning (SSL) approaches like BeiT and MAE, how to learn good representations by masking random patches of the input image and reconstructing the missing information has grown in concern. However, BeiT and PeCo need a "pre-pretraining" stage to produce discrete codebooks for masked patches ...
Yabo Chen +6 more
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Point Cloud Instance Segmentation with Inaccurate Bounding-Box Annotations
Sensors, 2023 Most existing point cloud instance segmentation methods require accurate and dense point-level annotations, which are extremely laborious to collect.
Yinyin Peng, Hui Feng, Tao Chen, Bo Hu
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Carbon nanotube based composite membranes for water desalination by membrane distillation [PDF]
, 2010 New technologies are required to improve desalination efficiency and increase water treatment capacities. One promising low energy technique to produce potable water from either sea or sewage water is membrane distillation (MD).
Ludovic Dumée +11 more
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New double column system for heteroazeotropic batch distillation [PDF]
, 2009 A new double column system (DCS) operated in closed mode is suggested for heterogeneous batch distillation. This configuration is investigated by feasibility studies based on the assumption of maximal separation and is compared with the traditional batch
Denes, F. +5 more
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