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07/31/2023
UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming
Deep learning models have demonstrated impressive performance in various...
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05/23/2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
Byzantine-robust distributed learning (BRDL), in which computing devices...
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03/17/2023
GNNFormer: A Graph-based Framework for Cytopathology Report Generation
Cytopathology report generation is a necessary step for the standardized...
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03/09/2023
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning
Federated learning (FL) has recently become a hot research topic, in whi...
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03/01/2023
Asymmetric Learning for Graph Neural Network based Link Prediction
Link prediction is a fundamental problem in many graph based application...
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09/23/2022
Optimizing Class Distribution in Memory for Multi-Label Online Continual Learning
Online continual learning, especially when task identities and task boun...
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10/19/2021
State-based Episodic Memory for Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) algorithms have made promising...
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09/13/2021
Cross Domain Robot Imitation with Invariant Representation
Animals are able to imitate each others' behavior, despite their differe...
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08/04/2020
Multiple Code Hashing for Efficient Image Retrieval
Due to its low storage cost and fast query speed, hashing has been widel...
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08/04/2020
ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval
Retrieving content relevant images from a large-scale fine-grained datas...
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07/28/2020
Stochastic Normalized Gradient Descent with Momentum for Large Batch Training
Stochastic gradient descent (SGD) and its variants have been the dominat...
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05/11/2020
TOMA: Topological Map Abstraction for Reinforcement Learning
Animals are able to discover the topological map (graph) of surrounding ...
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03/02/2020
BASGD: Buffered Asynchronous SGD for Byzantine Learning
Distributed learning has become a hot research topic, due to its wide ap...
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02/26/2020
Stagewise Enlargement of Batch Size for SGD-based Learning
Existing research shows that the batch size can seriously affect the per...
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07/01/2019
Weight Normalization based Quantization for Deep Neural Network Compression
With the development of deep neural networks, the size of network models...
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06/11/2019
ADASS: Adaptive Sample Selection for Training Acceleration
Stochastic gradient decent (SGD) and its variants, including some accele...
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06/06/2019
Clustered Reinforcement Learning
Exploration strategy design is one of the challenging problems in reinfo...
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05/30/2019
On the Convergence of Memory-Based Distributed SGD
Distributed stochastic gradient descent (DSGD) has been widely used for ...
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05/30/2019
Global Momentum Compression for Sparse Communication in Distributed SGD
With the rapid growth of data, distributed stochastic gradient descent (...
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05/27/2019
Deep Multi-Index Hashing for Person Re-Identification
Traditional person re-identification (ReID) methods typically represent ...
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05/27/2019
On the Evaluation Metric for Hashing
Due to its low storage cost and fast query speed, hashing has been widel...
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05/27/2019
Collaborative Self-Attention for Recommender Systems
Recommender systems (RS), which have been an essential part in a wide ra...
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05/26/2019
Gated Group Self-Attention for Answer Selection
Answer selection (answer ranking) is one of the key steps in many kinds ...
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05/26/2019
Hashing based Answer Selection
Answer selection is an important subtask of question answering (QA), whe...
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01/10/2019
Quantized Epoch-SGD for Communication-Efficient Distributed Learning
Due to its efficiency and ease to implement, stochastic gradient descent...
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03/15/2018
Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate
Distributed sparse learning with a cluster of multiple machines has attr...
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03/02/2018
Convolutional Geometric Matrix Completion
Geometric matrix completion (GMC) has been proposed for recommendation b...
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02/10/2018
Feature-Distributed SVRG for High-Dimensional Linear Classification
Linear classification has been widely used in many high-dimensional appl...
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07/26/2017
Asymmetric Deep Supervised Hashing
Hashing has been widely used for large-scale approximate nearest neighbo...
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06/19/2016
Full-Time Supervision based Bidirectional RNN for Factoid Question Answering
Recently, bidirectional recurrent neural network (BRNN) has been widely ...
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01/31/2016
A Proximal Stochastic Quasi-Newton Algorithm
In this paper, we discuss the problem of minimizing the sum of two conve...
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01/30/2016
SCOPE: Scalable Composite Optimization for Learning on Spark
Many machine learning models, such as logistic regression (LR) and suppo...
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11/12/2015
Feature Learning based Deep Supervised Hashing with Pairwise Labels
Recent years have witnessed wide application of hashing for large-scale ...
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10/26/2015
A Parallel algorithm for X-Armed bandits
The target of X-armed bandit problem is to find the global maximum of an...
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08/24/2015
