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Kaiwen Zhou
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2020 – today
- 2024
- [j4]Kaiwen Zhou, Jianhong Zhou, Yuxiang Tang, Jiahua Li, Zhiliang Hong, Jiawei Xu:
A 0.00055% THD + N Class-D Audio Amplifier With Capacitive Feedforward PWM and Wide-Band Aliasing Reduction. IEEE J. Solid State Circuits 59(12): 4045-4056 (2024) - [j3]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: 109925 (2024) - [j2]Khurram Shahzad, Rui Wang, Yichen Feng, Kaiwen Zhou:
Geometric algebra and cosine-function based variable step-size adaptive filtering algorithms. Signal Image Video Process. 18(11): 7641-7654 (2024) - [c24]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. AAAI 2024: 16040-16048 - [c23]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: 6845-6863 - [c22]Kaiwen Zhou, Kwonjoon Lee, Teruhisa Misu, Xin Wang:
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models. ACL (Findings) 2024: 10783-10795 - [c21]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: 1-2 - [c20]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 - [c19]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: 380-382 - [c18]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: 1002-1016 - [i31]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR abs/2401.08464 (2024) - [i30]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 abs/2401.15847 (2024) - [i29]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 abs/2402.03139 (2024) - [i28]Kaiwen Zhou, Tianyu Wang:
Personalized Interiors at Scale: Leveraging AI for Efficient and Customizable Design Solutions. CoRR abs/2405.19188 (2024) - [i27]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 abs/2407.18035 (2024) - [i26]Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, Anderson Compalas, Dawn Song, Xin Eric Wang:
Multimodal Situational Safety. CoRR abs/2410.06172 (2024) - [i25]Jingxuan Chen, Derek Yuen, Bin Xie, Yuhao Yang, Gongwei Chen, Zhihao Wu, Li Yixing, Xurui Zhou, Weiwen Liu, Shuai Wang, Kaiwen Zhou, Rui Shao, Liqiang Nie, Yasheng Wang, Jianye Hao, Jun Wang, Kun Shao:
SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation. CoRR abs/2410.15164 (2024) - 2023
- [c17]Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen:
A Novel Extrapolation Technique to Accelerate WMMSE. ICASSP 2023: 1-5 - [c16]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 - [c15]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: 42829-42842 - [c14]Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS 2023 - [c13]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS 2023 - [i24]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 abs/2301.13166 (2023) - [i23]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR abs/2304.11327 (2023) - [i22]Kaiwen Zhou, Kwonjoon Lee, Teruhisa Misu, Xin Eric Wang:
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models. CoRR abs/2310.05872 (2023) - [i21]Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR abs/2310.19035 (2023) - [i20]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 abs/2311.18194 (2023) - 2022
- [c12]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. AISTATS 2022: 3684-3708 - [c11]Kaiwen Zhou, Xin Eric Wang:
FedVLN: Privacy-Preserving Federated Vision-and-Language Navigation. ECCV (36) 2022: 682-699 - [c10]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: 7144-7163 - [c9]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: 21360-21379 - [i19]Kaiwen Zhou, Xin Eric Wang:
FedVLN: Privacy-preserving Federated Vision-and-Language Navigation. CoRR abs/2203.14936 (2022) - [i18]Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng:
An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. CoRR abs/2205.02273 (2022) - [i17]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 abs/2206.07314 (2022) - [i16]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng:
Pareto Invariant Risk Minimization. CoRR abs/2206.07766 (2022) - [i15]Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang:
Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR abs/2206.13011 (2022) - [i14]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 abs/2208.13266 (2022) - [i13]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 abs/2211.14769 (2022) - 2021
- [i12]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. CoRR abs/2105.12062 (2021) - [i11]Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng:
Local Reweighting for Adversarial Training. CoRR abs/2106.15776 (2021) - [i10]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. CoRR abs/2109.15292 (2021) - 2020
- [j1]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): 188-202 (2020) - [c8]Qinghua Ding, Kaiwen Zhou, James Cheng:
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. IJCAI 2020: 3276-3282 - [c7]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. NeurIPS 2020 - [c6]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng:
Convolutional Embedding for Edit Distance. SIGIR 2020: 599-608 - [c5]Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng:
Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. UAI 2020: 211-220 - [i9]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng:
Edit Distance Embedding using Convolutional Neural Networks. CoRR abs/2001.11692 (2020) - [i8]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates. CoRR abs/2005.12061 (2020)
2010 – 2019
- 2019
- [c4]Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo:
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS 2019: 1602-1610 - [i7]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 abs/1911.04655 (2019) - 2018
- [c3]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. ACML 2018: 815-830 - [c2]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: 1027-1036 - [c1]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. ICML 2018: 5975-5984 - [i6]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 abs/1802.09932 (2018) - [i5]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR abs/1802.09933 (2018) - [i4]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. CoRR abs/1806.11027 (2018) - [i3]Kaiwen Zhou:
Direct Acceleration of SAGA using Sampled Negative Momentum. CoRR abs/1806.11048 (2018) - [i2]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. CoRR abs/1810.03105 (2018) - [i1]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 abs/1810.09104 (2018)
Coauthor Index
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last updated on 2024-12-17 21:50 CET by the dblp team
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