← Authors

James T. Kwok

32 papers · 2005–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (19) 🐝 Cross-Pollinator (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (20) 🌟 Keyword Trendsetter Combo (7) πŸ† Grand Slam πŸ‘₯ Mega-Team (30) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ—ƒοΈ Keyword Collector (169) πŸš€ Conference Pioneer πŸ’Ž Century Club (32) πŸ”₯ Unstoppable (11) πŸ“ˆ Trend Setter

Conferences

NIPS (14) IJCAI (6) JMLR (5) AAAI (2) ICLR (2) CVPR (1) ICCV (1) ICML (1)

Top co-authors

Quanming Yao (6) Ivor W. Tsang (5) Yu Zhang (4) Weisen Jiang (3) Lu Hou (3) Lifeng Shen (2) Han Shi (2) Shuai Zheng (2) Bo Han (2) Xiaofeng Cao (2)

Keywords

kernel methods (3) representation learning (3) semi-supervised learning (2) core vector machine (2) few-shot learning (2) stochastic optimization (2) convergence rate (2) online learning (2) nonconvex regularization (2) large language model (2) convex optimization (2) graph convolutional network (2) mixture model (2) support vector machine (2) nonconvex optimization (1) model selection (1) contrastive learning (1) unsupervised learning (1) link prediction (1) anomaly detection (1)

Papers

EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions CVPR 2025
Depth Any Event Stream: Enhancing Event-based Monocular Depth Estimation via Dense-to-Sparse Distillation ICCV 2025
Mentored Learning: Improving Generalization and Convergence of Student Learner JMLR 2024
GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning NIPS 2024
RouterDC: Query-Based Router by Dual Contrastive Learning for Assembling Large Language Models NIPS 2024
Nonparametric Teaching for Multiple Learners NIPS 2023
Efficient Hyper-parameter Optimization with Cubic Regularization NIPS 2023
Multi-Objective Deep Learning with Adaptive Reference Vectors NIPS 2022
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization JMLR 2022
Time Series Anomaly Detection with Multiresolution Ensemble Decoding AAAI 2021
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation NIPS 2021
Effective Meta-Regularization by Kernelized Proximal Regularization NIPS 2021
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network NIPS 2020
Effective Decoding in Graph Auto-Encoder Using Triadic Closure AAAI 2020
Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS NIPS 2020
Analysis of Quantized Models ICLR 2019
Loss-aware Weight Quantization of Deep Networks ICLR 2018
Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity JMLR 2018
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems IJCAI 2017
Follow the Moving Leader in Deep Learning ICML 2017
Greedy Learning of Generalized Low-Rank Models IJCAI 2016
Fast-and-Light Stochastic ADMM IJCAI 2016
Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion IJCAI 2015
Convex and Scalable Weakly Labeled SVMs JMLR 2013
Efficient Kernel Learning from Side Information Using ADMM IJCAI 2013
Accurate Probability Calibration for Multiple Classifiers IJCAI 2013
Priors for Diversity in Generative Latent Variable Models NIPS 2012
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification NIPS 2012
Accelerated Gradient Methods for Stochastic Optimization and Online Learning NIPS 2009
Large-Scale Sparsified Manifold Regularization NIPS 2006
Simplifying Mixture Models through Function Approximation NIPS 2006
Core Vector Machines: Fast SVM Training on Very Large Data Sets JMLR 2005