2025
Quality-aware fuzzy min-max neural networks for dynamic brain network analysis and its application to schizophrenia identification.
Appl. Soft Comput., 2025
2024
FMDNN: A Fuzzy-Guided Multigranular Deep Neural Network for Histopathological Image Classification.
IEEE Trans. Fuzzy Syst., August, 2024
False Correlation Reduction for Offline Reinforcement Learning.
IEEE Trans. Pattern Anal. Mach. Intell., February, 2024
A Time-Consistency Curriculum for Learning From Instance-Dependent Noisy Labels.
IEEE Trans. Pattern Anal. Mach. Intell., 2024
FDiff-Fusion: Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation.
Inf. Fusion, 2024
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CoRR, 2024
Florence-VL: Enhancing Vision-Language Models with Generative Vision Encoder and Depth-Breadth Fusion.
CoRR, 2024
DynaSaur: Large Language Agents Beyond Predefined Actions.
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CoRR, 2024
Reweighting Local Mimina with Tilted SAM.
CoRR, 2024
Hybrid Memory Replay: Blending Real and Distilled Data for Class Incremental Learning.
CoRR, 2024
BenTo: Benchmark Task Reduction with In-Context Transferability.
CoRR, 2024
Diffusion Curriculum: Synthetic-to-Real Generative Curriculum Learning via Image-Guided Diffusion.
CoRR, 2024
WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents.
CoRR, 2024
From Lists to Emojis: How Format Bias Affects Model Alignment.
CoRR, 2024
Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach.
CoRR, 2024
M2EF-NNs: Multimodal Multi-instance Evidence Fusion Neural Networks for Cancer Survival Prediction.
CoRR, 2024
FDiff-Fusion:Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation.
CoRR, 2024
FMDNN: A Fuzzy-guided Multi-granular Deep Neural Network for Histopathological Image Classification.
CoRR, 2024
UniGen: A Unified Framework for Textual Dataset Generation Using Large Language Models.
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CoRR, 2024
MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries?
CoRR, 2024
RuleR: Improving LLM Controllability by Rule-based Data Recycling.
CoRR, 2024
1+1>2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?
CoRR, 2024
GenQA: Generating Millions of Instructions from a Handful of Prompts.
CoRR, 2024
OPTune: Efficient Online Preference Tuning.
CoRR, 2024
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise.
CoRR, 2024
Multi-Level Additive Modeling for Structured Non-IID Federated Learning.
CoRR, 2024
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement.
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CoRR, 2024
Mosaic IT: Enhancing Instruction Tuning with Data Mosaics.
CoRR, 2024
Many-Objective Multi-Solution Transport.
CoRR, 2024
Meta-Task Prompting Elicits Embedding from Large Language Models.
CoRR, 2024
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers.
CoRR, 2024
A Survey on Knowledge Distillation of Large Language Models.
CoRR, 2024
MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion.
CoRR, 2024
TrustLLM: Trustworthiness in Large Language Models.
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CoRR, 2024
When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions.
Proceedings of the ACM on Web Conference 2024, 2024
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization.
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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024
An End-to-End Submodular Framework for Data-Efficient In-Context Learning.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024
GPFedRec: Graph-Guided Personalization for Federated Recommendation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Task-Driven Domain-Agnostic Learning with Information Bottleneck for Autonomous Steering.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Position: TrustLLM: Trustworthiness in Large Language Models.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
ODIN: Disentangled Reward Mitigates Hacking in RLHF.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Federated Recommendation with Additive Personalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
AlpaGasus: Training a Better Alpaca with Fewer Data.
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Proceedings of the Twelfth International Conference on Learning Representations, 2024
AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models.
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Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
SpecHub: Provable Acceleration to Multi-Draft Speculative Decoding.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
1+1\textgreater2: Can Large Language Models Serve as Cross-Lingual Knowledge Aggregators?
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Do Text-Free Diffusion Models Learn Discriminative Visual Representations?
Proceedings of the Computer Vision - ECCV 2024, 2024
Understanding the Impact of Negative Prompts: When and How Do They Take Effect?
Proceedings of the Computer Vision - ECCV 2024, 2024
Corpus-Steered Query Expansion with Large Language Models.
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024
Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Hallusionbench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Automatic Curriculum for Unsupervised Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024
Multi-Objective Linguistic Control of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Meta-Task Prompting Elicits Embeddings from Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Retrieval-Augmented Retrieval: Large Language Models are Strong Zero-Shot Retriever.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
Multi-center federated learning: clients clustering for better personalization.
World Wide Web (WWW), January, 2023
Curriculum Learning: from Human Strategies to Learning Dynamics
PhD thesis, 2023
Good Questions Help Zero-Shot Image Reasoning.
CoRR, 2023
Do text-free diffusion models learn discriminative visual representations?
CoRR, 2023
AerialBooth: Mutual Information Guidance for Text Controlled Aerial View Synthesis from a Single Image.
CoRR, 2023
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models.
CoRR, 2023
Reflection-Tuning: Data Recycling Improves LLM Instruction-Tuning.
CoRR, 2023
NLPBench: Evaluating Large Language Models on Solving NLP Problems.
CoRR, 2023
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution.
CoRR, 2023
MerA: Merging Pretrained Adapters For Few-Shot Learning.
CoRR, 2023
Diffusion Models Beat GANs on Image Classification.
CoRR, 2023
Taming Small-sample Bias in Low-budget Active Learning.
CoRR, 2023
Condensed Prototype Replay for Class Incremental Learning.
CoRR, 2023
Reinforcement Learning finetuned Vision-Code Transformer for UI-to-Code Generation.
CoRR, 2023
Spatial-temporal Prompt Learning for Federated Weather Forecasting.
CoRR, 2023
IFedRec: Item-Guided Federated Aggregation for Cold-Start.
CoRR, 2023
Graph-guided Personalization for Federated Recommendation.
CoRR, 2023
Large Language Models are Strong Zero-Shot Retriever.
CoRR, 2023
When do you need Chain-of-Thought Prompting for ChatGPT?
CoRR, 2023
Aerial Diffusion: Text Guided Ground-to-Aerial View Translation from a Single Image using Diffusion Models.
CoRR, 2023
It Takes One to Tango but More Make Trouble? The Number of Demonstrations Needed for In-Context Learning.
CoRR, 2023
Aerial Diffusion: Text Guided Ground-to-Aerial View Synthesis from a Single Image using Diffusion Models.
Proceedings of the SIGGRAPH Asia 2023 Technical Communications, 2023
Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Structured Federated Learning through Clustered Additive Modeling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Dual Personalization on Federated Recommendation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Does Continual Learning Equally Forget All Parameters?
Proceedings of the International Conference on Machine Learning, 2023
Continual Task Allocation in Meta-Policy Network via Sparse Prompting.
Proceedings of the International Conference on Machine Learning, 2023
Structured Cooperative Learning with Graphical Model Priors.
Proceedings of the International Conference on Machine Learning, 2023
When to Learn What: Model-Adaptive Data Augmentation Curriculum.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Subclass-balancing Contrastive Learning for Long-tailed Recognition.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Merging Experts into One: Improving Computational Efficiency of Mixture of Experts.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
How Many Demonstrations Do You Need for In-context Learning?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
2022
Extracting Local Reasoning Chains of Deep Neural Networks.
Trans. Mach. Learn. Res., 2022
Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy.
IEEE Trans. Knowl. Data Eng., 2022
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels.
CoRR, 2022
Personalized Federated Learning With Structure.
CoRR, 2022
On the Convergence of Clustered Federated Learning.
CoRR, 2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Federated Learning from Pre-Trained Models: A Contrastive Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Retrospective Adversarial Replay for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Phrase-level Textual Adversarial Attack with Label Preservation.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022
Personalized Federated Learning With a Graph.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Identity-Disentangled Adversarial Augmentation for Self-supervised Learning.
Proceedings of the International Conference on Machine Learning, 2022
EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022
Pareto Policy Pool for Model-based Offline Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Diverse Client Selection for Federated Learning via Submodular Maximization.
Proceedings of the Tenth International Conference on Learning Representations, 2022
TASA: Deceiving Question Answering Models by Twin Answer Sentences Attack.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Learning to Collaborate in Decentralized Learning of Personalized Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Token Dropping for Efficient BERT Pretraining.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
FedProto: Federated Prototype Learning across Heterogeneous Clients.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
FedProto: Federated Prototype Learning over Heterogeneous Devices.
CoRR, 2021
Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion.
Proceedings of the WWW '21: The Web Conference 2021, 2021
Class-Disentanglement and Applications in Adversarial Detection and Defense.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Constrained Robust Submodular Partitioning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Robust Curriculum Learning: from clean label detection to noisy label self-correction.
Proceedings of the 9th International Conference on Learning Representations, 2021
Isometric Propagation Network for Generalized Zero-shot Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly.
Proceedings of the 9th International Conference on Learning Representations, 2021
Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
Curriculum Learning by Optimizing Learning Dynamics.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Multi-Center Federated Learning.
CoRR, 2020
Semantic Triple Encoder for Fast Open-Set Link Prediction.
CoRR, 2020
Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline.
CoRR, 2020
Conditional Self-Attention for Query-based Summarization.
CoRR, 2020
Curriculum Learning by Dynamic Instance Hardness.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Time-Consistent Self-Supervision for Semi-Supervised Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention.
Proceedings of the 28th International Conference on Computational Linguistics, 2020
Attribute Propagation Network for Graph Zero-Shot Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Data Subset Selection With Imperfect Multiple Labels.
IEEE Trans. Neural Networks Learn. Syst., 2019
Learning to Propagate for Graph Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Curriculum-guided Hindsight Experience Replay.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Jumpout : Improved Dropout for Deep Neural Networks with ReLUs.
Proceedings of the 36th International Conference on Machine Learning, 2019
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Fast Directional Self-Attention Mechanism.
CoRR, 2018
Diverse Ensemble Evolution: Curriculum Data-Model Marriage.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Minimax Curriculum Learning: Machine Teaching with Desirable Difficulties and Scheduled Diversity.
Proceedings of the 6th International Conference on Learning Representations, 2018
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling.
Proceedings of the 6th International Conference on Learning Representations, 2018
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
Scaling Submodular Maximization via Pruned Submodularity Graphs.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Stream Clipper: Scalable Submodular Maximization on Stream.
CoRR, 2016
2015
Efficient Robust Conditional Random Fields.
IEEE Trans. Image Process., 2015
2014
Minimizing Nearest Neighbor Classification Error for Nonparametric Dimension Reduction.
IEEE Trans. Neural Networks Learn. Syst., 2014
Divide-and-Conquer Learning by Anchoring a Conical Hull.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Multi-task copula by sparse graph regression.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
2013
Double Shrinking Sparse Dimension Reduction.
IEEE Trans. Image Process., 2013
Unmixing Incoherent Structures of Big Data by Randomized or Greedy Decomposition.
CoRR, 2013
Constrained stochastic gradient descent for large-scale least squares problem.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013
k-bit Hamming compressed sensing.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013
Shifted Subspaces Tracking on Sparse Outlier for Motion Segmentation.
Proceedings of the IJCAI 2013, 2013
Divide-and-Conquer Anchoring for Near-Separable Nonnegative Matrix Factorization and Completion in High Dimensions.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013
Greedy Bilateral Sketch, Completion & Smoothing.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013
2012
Compressed labeling on distilled labelsets for multi-label learning.
Mach. Learn., 2012
Multi-label Subspace Ensemble.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Labelset anchored subspace ensemble (LASE) for multi-label annotation.
Proceedings of the International Conference on Multimedia Retrieval, 2012
1-bit Hamming compressed sensing.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
Bilateral random projections.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
2011
Manifold elastic net: a unified framework for sparse dimension reduction.
Data Min. Knowl. Discov., 2011
Hamming Compressed Sensing
CoRR, 2011
Multi-label Learning via Structured Decomposition and Group Sparsity
CoRR, 2011
GoDec: Randomized Lowrank & Sparse Matrix Decomposition in Noisy Case.
Proceedings of the 28th International Conference on Machine Learning, 2011
2010
Backward-Forward Least Angle Shrinkage for Sparse Quadratic Optimization.
Proceedings of the Neural Information Processing. Theory and Algorithms, 2010
NESVM: A Fast Gradient Method for Support Vector Machines.
Proceedings of the ICDM 2010, 2010
2009
Manifold Elastic Net for Sparse Learning.
Proceedings of the IEEE International Conference on Systems, 2009