Kaiwen Zhou

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 55

Top Topics

Risk Minimization

Convolutional Neural Networks

Embodied Agents

Top Venues

Publications

Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. AAAI (2024)
Kaiwen Zhou, Tianyu Wang
Personalized Interiors at Scale: Leveraging AI for Efficient and Customizable Design Solutions. CoRR (2024)
Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, Lei Zhu
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models. CoRR (2024)
Kaiwen Zhou, Kwonjoon Lee, Teruhisa Misu, Xin Wang
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models. ACL (Findings) (2024)
Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR (2024)
Jianhong Zhou, Yijie Li, Kaiwen Zhou, Yuying Li, Tian Dong, Zhiliang Hong, Jiawei Xu
A 103.6dB-SNDR 760mVPP-Input-Range 7.8GΩ-Input-Impedance Direct-Digitization Sensor Readout with Pseudo-Differential Transconductors and Dummy DAC. CICC (2024)
Kaiwen Zhou, Jianhong Zhou, Yuxiang Tang, Jiahua Li, Zhiliang Hong, Jiawei Xu
21.2 A 0.81mA, -105.2dB THD+N Class-D Audio Amplifier with Capacitive Feedforward and PWM-Aliasing Reduction for Wide-Band-Effective Linearity Improvement. ISSCC (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR (2024)
Kaiwen Zhou, Wenbin Xing, Jingbo Wang, Huanhuan Li, Zaili Yang
A data-driven risk model for maritime casualty analysis: A global perspective. Reliab. Eng. Syst. Saf. 244 (2024)
Yue Fan, Jing Gu, Kaiwen Zhou, Qianqi Yan, Shan Jiang, Ching-Chen Kuo, Yang Zhao, Xinze Guan, Xin Wang
Muffin or Chihuahua? Challenging Multimodal Large Language Models with Multipanel VQA. ACL (1) (2024)
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR (2024)
Yue Fan, Jing Gu, Kaiwen Zhou, Qianqi Yan, Shan Jiang, Ching-Chen Kuo, Xinze Guan, Xin Eric Wang
Muffin or Chihuahua? Challenging Large Vision-Language Models with Multipanel VQA. CoRR (2024)
Yunchao Zhang, Zonglin Di, Kaiwen Zhou, Cihang Xie, Xin Wang
Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning. NAACL-HLT (2024)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR (2023)
Kaiwen Zhou, Kaizhi Zheng, Connor Pryor, Yilin Shen, Hongxia Jin, Lise Getoor, Xin Eric Wang
ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation. CoRR (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR (2023)
Kaiwen Zhou, Kwonjoon Lee, Teruhisa Misu, Xin Eric Wang
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models. CoRR (2023)
Kaiwen Zhou, Kaizhi Zheng, Connor Pryor, Yilin Shen, Hongxia Jin, Lise Getoor, Xin Eric Wang
ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation. ICML (2023)
Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS (2023)
Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen
A Novel Extrapolation Technique to Accelerate WMMSE. ICASSP (2023)
Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS (2023)
Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR (2023)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR (2023)
Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang
Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR (2022)
Kaiwen Zhou, Xin Eric Wang
FedVLN: Privacy-preserving Federated Vision-and-Language Navigation. CoRR (2022)
Kaiwen Zhou, Xin Eric Wang
FedVLN: Privacy-Preserving Federated Vision-and-Language Navigation. ECCV (36) (2022)
Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. AISTATS (2022)
Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng
Pareto Invariant Risk Minimization. CoRR (2022)
Lai Tian, Kaiwen Zhou, Anthony Man-Cho So
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions. ICML (2022)
Kaizhi Zheng, Kaiwen Zhou, Jing Gu, Yue Fan, Jialu Wang, Zonglin Di, Xuehai He, Xin Eric Wang
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents. CoRR (2022)
Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. CoRR (2022)
Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng
An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. CoRR (2022)
Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. ICML (2022)
Yunchao Zhang, Zonglin Di, Kaiwen Zhou, Cihang Xie, Xin Wang
Navigation as the Attacker Wishes? Towards Building Byzantine-Robust Embodied Agents under Federated Learning. CoRR (2022)
Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng
Local Reweighting for Adversarial Training. CoRR (2021)
Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. CoRR (2021)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. CoRR (2021)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. NeurIPS (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Convolutional Embedding for Edit Distance. SIGIR (2020)
Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng
Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. UAI (2020)
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates. CoRR (2020)
Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32 (1) (2020)
Qinghua Ding, Kaiwen Zhou, James Cheng
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. IJCAI (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng
Edit Distance Embedding using Convolutional Neural Networks. CoRR (2020)
Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR (2019)
Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS (2019)
Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin
ASVRG: Accelerated Proximal SVRG. CoRR (2018)
Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin
ASVRG: Accelerated Proximal SVRG. ACML (2018)
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS (2018)
Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR (2018)
Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR (2018)
Kaiwen Zhou, Fanhua Shang, James Cheng
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. ICML (2018)
Xiao Yan, Xinyan Dai, Jie Liu, Kaiwen Zhou, James Cheng
Norm-Range Partition: A Univiseral Catalyst for LSH based Maximum Inner Product Search (MIPS). CoRR (2018)
Kaiwen Zhou
Direct Acceleration of SAGA using Sampled Negative Momentum. CoRR (2018)
Kaiwen Zhou, Fanhua Shang, James Cheng
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. CoRR (2018)