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James T. Kwok

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

Achievements

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+13 more ↓ 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (19) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8)
🧭 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