← Authors

Ke Tang

33 papers · 2015–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) πŸƒ Academic Marathon (10) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) πŸ—ΊοΈ Taxonomy Completionist (50) 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ”¬ Deep Specialist (12) πŸ’Ž Century Club (33) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (132) ⚑ Prolific Year (8) πŸ”₯ Unstoppable (11)

Conferences

IJCAI (13) AAAI (6) NIPS (6) ICML (3) ACL (1) CVPR (1) ICCV (1) ICLR (1) JMLR (1)

Top co-authors

Chao Qian (11) Xin Yao (7) Yang Yu (6) Zhi-Hua Zhou (4) Shengcai Liu (4) Jing-Cheng Shi (4) Yunwen Lei (4) Guiying Li (3) Liangpeng Zhang (3) Chao Feng (3)

Keywords

subset selection (4) greedy algorithm (3) combinatorial optimization (3) model compression (3) pareto optimization (3) submodular function (3) adversarial robustness (3) approximation guarantee (2) deep neural network (2) stochastic gradient descent (2) stochastic optimization (2) generalization bound (2) multi-objective optimization (2) robustness evaluation (2) reconstruction error (2) mirror descent (2) submodular optimization (2) adversarial attack (2) approximation algorithm (2) approximation ratio (2)

Papers

Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models AAAI 2025
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets ICML 2025
Approximation to Smooth Functions by Low-Rank Swish Networks ICML 2025
SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization ICLR 2025
Mitigating Catastrophic Overfitting in Fast Adversarial Training via Label Information Elimination ICCV 2025
Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS Demosaicing CVPR 2025
Efficient Robustness Evaluation via Constraint Relaxation AAAI 2025
DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems ICML 2024
Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization ACL 2024
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles AAAI 2023
Causality-driven Hierarchical Structure Discovery for Reinforcement Learning NIPS 2022
Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions JMLR 2021
Towards Robust Dynamic Network Embedding IJCAI 2021
On Performance Estimation in Automatic Algorithm Configuration AAAI 2020
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping AAAI 2019
Explicit Planning for Efficient Exploration in Reinforcement Learning NIPS 2019
Optimal Stochastic and Online Learning with Individual Iterates NIPS 2019
Unsupervised Feature Selection by Pareto Optimization AAAI 2019
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities NIPS 2018
A General Approach to Running Time Analysis of Multi-objective Evolutionary Algorithms IJCAI 2018
Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection IJCAI 2018
Sequence Selection by Pareto Optimization IJCAI 2018
Distributed Pareto Optimization for Subset Selection IJCAI 2018
Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error IJCAI 2018
Generalization Bounds for Regularized Pairwise Learning IJCAI 2018
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression IJCAI 2018
Optimizing Ratio of Monotone Set Functions IJCAI 2017
On Subset Selection with General Cost Constraints IJCAI 2017
Subset Selection under Noise NIPS 2017
Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning NIPS 2017
Parallel Pareto Optimization for Subset Selection IJCAI 2016
Increasingly Cautious Optimism for Practical PAC-MDP Exploration IJCAI 2015
Active Learning from Crowds with Unsure Option IJCAI 2015