Area of research
Computer Vision and Pattern Recognition · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Parallel computing, Speedup, Architecture, and Code (set theory).
Efficient Dataset Distillation via Minimax Diffusion
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models
DREAM: Efficient Dataset Distillation by Representative Matching
An Evidential Multi-Target Domain Adaptation Method Based on Weighted Fusion for Cross-Domain Pattern Classification
An evidential combination method with multi-color spaces for remote sensing image scene classification
BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency
Sequence Parallelism: Long Sequence Training from System Perspective
Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency
CAFE: Learning to Condense Dataset by Aligning Features
Crafting Better Contrastive Views for Siamese Representation Learning
Towards Efficient and Scalable Sharpness-Aware Minimization
Go Wider Instead of Deeper
Tesseract: Parallelize the Tensor Parallelism Efficiently
Parallel Training of Pre-Trained Models via Chunk-Based Dynamic Memory Management
An ultrasensitive probe-free electrochemical immunosensor for gibberellins employing polydopamine-antibody nanoparticles modified electrode
Development of a panel of three multiplex allele-specific qRT-PCR assays for quick differentiation of recombinant variants and Omicron subvariants of SARS-CoV-2
Evidential instance selection for K-nearest neighbor classification of big data
Multitask Learning for Visual Question Answering
Wideband Full-Corporate-Feed Waveguide Continuous Transverse Stub Antenna Array
Designing a Heuristic Cross-Architecture Combination for Breadth-First Search