default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDaniel Kang 0001
Daniel D. Kang
Person information
- affiliation: University of Illinois Urbana Champaign, Champaign, IL, USA
- affiliation (2022 - 2023): University of California, Berkeley, CA, USA
- affiliation (PhD 2022): Stanford University, CA, USA
Other persons with the same name
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2026
[c26]Tengjun Jin, Yoojin Choi, Yuxuan Zhu, Daniel Kang:
Text-to-SQL Benchmarks are Broken: An In-Depth Analysis of Annotation Errors. CIDR 2026- 2025
- [j17]Daniel Kang:
Analytical Queries for Unstructured Data. Found. Trends Databases 15(2): 115-196 (2025) - [j16]Yuxuan Zhu
, Tengjun Jin, Stefanos Baziotis, Chengsong Zhang, Charith Mendis, Daniel D. Kang:
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees. Proc. ACM Manag. Data 3(3): 198:1-198:28 (2025) - [j15]Chuxuan Hu, Maxwell Yang, James Weiland, Yeji Lim, Suhas Palawala, Daniel D. Kang:
Drama : Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries. Proc. ACM Manag. Data 3(6): 1-28 (2025) - [c25]Boxi Yu, Yuxuan Zhu, Pinjia He, Daniel Kang:
UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench. ACL (1) 2025: 3762-3774 - [c24]Chuxuan Hu, Liyun Zhang, Yeji Lim, Aum Wadhwani, Austin Peters, Daniel Kang:
REPRO-Bench: Can Agentic AI Systems Assess the Reproducibility of Social Science Research? ACL (Findings) 2025: 23616-23626 - [c23]Yuxuan Zhu, Daniel Kang:
Efficient Approximate Query Processing with Block Sampling. CIDR 2025 - [c22]Yuxuan Zhu, Antony Kellermann, Dylan Bowman, Philip Li, Akul Gupta, Adarsh Danda, Richard Fang, Conner Jensen, Eric Ihli, Jason Benn, Jet Geronimo, Avi Dhir, Sudhit Rao, Kaicheng Yu, Twm Stone, Daniel Kang:
CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities. ICML 2025 - [c21]Qiusi Zhan, Richard Fang, Henil Shalin Panchal, Daniel Kang:
Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. NAACL (Findings) 2025: 7101-7117 - [i52]Chuxuan Hu, Austin Peters, Daniel Kang:
LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data. CoRR abs/2501.03892 (2025) - [i51]Hyeonjeong Ha, Qiusi Zhan, Jeonghwan Kim, Dimitrios Bralios, Saikrishna Sanniboina, Nanyun Peng, Kai-Wei Chang, Daniel Kang, Heng Ji:
MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks. CoRR abs/2502.17832 (2025) - [i50]Qiusi Zhan, Richard Fang, Henil Shalin Panchal, Daniel Kang:
Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. CoRR abs/2503.00061 (2025) - [i49]Yuxuan Zhu, Antony Kellermann, Dylan Bowman, Philip Li, Akul Gupta, Adarsh Danda, Richard Fang, Conner Jensen, Eric Ihli, Jason Benn, Jet Geronimo, Avi Dhir, Sudhit Rao, Kaicheng Yu, Twm Stone, Daniel Kang:
CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities. CoRR abs/2503.17332 (2025) - [i48]Yuxuan Zhu, Tengjun Jin, Stefanos Baziotis, Chengsong Zhang, Charith Mendis, Daniel Kang:
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report). CoRR abs/2503.21087 (2025) - [i47]Tengjun Jin, Yuxuan Zhu, Daniel Kang:
ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines. CoRR abs/2504.04808 (2025) - [i46]Alex Broihier, Stefanos Baziotis, Daniel Kang, Charith Mendis:
PandasBench: A Benchmark for the Pandas API. CoRR abs/2506.02345 (2025) - [i45]Boxi Yu, Yuxuan Zhu, Pinjia He, Daniel Kang:
UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench. CoRR abs/2506.09289 (2025) - [i44]Chuxuan Hu, Yuxuan Zhu, Antony Kellermann, Caleb Biddulph, Suppakit Waiwitlikhit, Jason Benn, Daniel Kang:
Breaking Barriers: Do Reinforcement Post Training Gains Transfer To Unseen Domains? CoRR abs/2506.19733 (2025) - [i43]Yuxuan Zhu, Tengjun Jin, Yada Pruksachatkun, Andy Zhang, Shu Liu, Sasha Cui, Sayash Kapoor, Shayne Longpre, Kevin Meng, Rebecca Weiss, Fazl Barez, Rahul Gupta, Jwala Dhamala, Jacob Merizian, Mario Giulianelli, Harry Coppock, Cozmin Ududec, Jasjeet S. Sekhon, Jacob Steinhardt, Antony Kellerman, Sarah Schwettmann, Matei Zaharia, Ion Stoica, Percy Liang, Daniel Kang:
Establishing Best Practices for Building Rigorous Agentic Benchmarks. CoRR abs/2507.02825 (2025) - [i42]Bing-Jyue Chen, Lilia Tang, Daniel Kang:
ZKTorch: Compiling ML Inference to Zero-Knowledge Proofs via Parallel Proof Accumulation. CoRR abs/2507.07031 (2025) - [i41]Chuxuan Hu, Liyun Zhang, Yeji Lim, Aum Wadhwani, Austin Peters, Daniel Kang:
REPRO-Bench: Can Agentic AI Systems Assess the Reproducibility of Social Science Research? CoRR abs/2507.18901 (2025) - [i40]Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, Nitya Nadgir, Zachary S. Siegel, Boyi Wei, Tianci Xue, Ziru Chen, Felix Chen, Saiteja Utpala, Franck Ndzomga, Dheeraj Oruganty, Sophie Luskin, Kangheng Liu, Botao Yu, Amit Arora, Dongyoon Hahm, Harsh Trivedi, Huan Sun, Juyong Lee, Tengjun Jin, Yifan Mai, Yifei Zhou, Yuxuan Zhu, Rishi Bommasani, Daniel Kang, Dawn Song, Peter Henderson, Yu Su, Percy Liang, Arvind Narayanan:
Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation. CoRR abs/2510.11977 (2025) - [i39]Qiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, Xingzhi Guo, Daniel Kang, Joo-Kyung Kim:
SafeSearch: Do Not Trade Safety for Utility in LLM Search Agents. CoRR abs/2510.17017 (2025) - [i38]Chuxuan Hu, Maxwell Yang, James Weiland, Yeji Lim, Suhas Palawala, Daniel Kang:
DRAMA: Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries. CoRR abs/2510.27238 (2025) - [i37]Qiusi Zhan, Hyeonjeong Ha, Rui Yang, Sirui Xu, Hanyang Chen, Liang-Yan Gui, Yu-Xiong Wang, Huan Zhang, Heng Ji, Daniel Kang:
Visual Backdoor Attacks on MLLM Embodied Decision Making via Contrastive Trigger Learning. CoRR abs/2510.27623 (2025) - [i36]Daniel Kang:
Analytical Queries for Unstructured Data. CoRR abs/2511.03489 (2025) - [i35]Rohan Alur, Bradly C. Stadie, Daniel Kang, Ryan Chen, Matt McManus, Michael Rickert, Tyler Lee, Michael Federici, Richard Zhu, Dennis Fogerty, Hayley Williamson, Nina Lozinski, Aaron Linsky, Jasjeet S. Sekhon:
AIA Forecaster: Technical Report. CoRR abs/2511.07678 (2025) - [i34]Melissa Z. Pan, Negar Arabzadeh, Riccardo Cogo, Yuxuan Zhu, Alexander Xiong, Lakshya A. Agrawal, Huanzhi Mao, Emma Shen, Sid Pallerla, Liana Patel, Shu Liu, Tianneng Shi, Xiaoyuan Liu, Jared Quincy Davis, Emmanuele Lacavalla, Alessandro Basile, Shuyi Yang, Paul Castro, Daniel Kang, Joseph E. Gonzalez, Koushik Sen, Dawn Song, Ion Stoica, Matei Zaharia, Marquita Ellis:
Measuring Agents in Production. CoRR abs/2512.04123 (2025) - [i33]Bing-Jyue Chen, Lilia Tang, David Heath, Daniel Kang:
Linear-time and Logarithmically-sound Permutation and Multiset SNARKs. IACR Cryptol. ePrint Arch. 2025: 1967 (2025) - 2024
- [j14]Stefanos Baziotis, Daniel D. Kang, Charith Mendis:
Dias: Dynamic Rewriting of Pandas Code. Proc. ACM Manag. Data 2(1): 58:1-58:27 (2024) - [j13]Chuxuan Hu, Austin Peters, Daniel Kang:
LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data. Proc. VLDB Endow. 18(2): 253-264 (2024) - [c20]Qiusi Zhan, Zhixiang Liang, Zifan Ying, Daniel Kang:
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents. ACL (Findings) 2024: 10471-10506 - [c19]Timothy Dai, Austin Peters, Jonah B. Gelbach, David Freeman Engstrom, Daniel Kang:
tailwiz: Empowering Domain Experts with Easy-to-Use, Task-Specific Natural Language Processing Models. DEEM@SIGMOD 2024: 12-22 - [c18]Tengjun Jin, Akash Mittal, Chenghao Mo, Jiahao Fang, Chengsong Zhang, Timothy Dai, Daniel Kang:
AIDB: a Sparsely Materialized Database for Queries using Machine Learning. DEEM@SIGMOD 2024: 23-28 - [c17]Bing-Jyue Chen, Suppakit Waiwitlikhit, Ion Stoica, Daniel Kang:
ZKML: An Optimizing System for ML Inference in Zero-Knowledge Proofs. EuroSys 2024: 560-574 - [c16]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024 - [c15]Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang:
Trustless Audits without Revealing Data or Models. ICML 2024 - [c14]Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang:
Removing RLHF Protections in GPT-4 via Fine-Tuning. NAACL (Short Papers) 2024: 681-687 - [c13]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. SP (Workshops) 2024: 132-143 - [i32]Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang:
LLM Agents can Autonomously Hack Websites. CoRR abs/2402.06664 (2024) - [i31]Qiusi Zhan, Zhixiang Liang, Zifan Ying, Daniel Kang:
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents. CoRR abs/2403.02691 (2024) - [i30]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i29]Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang:
Trustless Audits without Revealing Data or Models. CoRR abs/2404.04500 (2024) - [i28]Richard Fang, Rohan Bindu, Akul Gupta, Daniel Kang:
LLM Agents can Autonomously Exploit One-day Vulnerabilities. CoRR abs/2404.08144 (2024) - [i27]Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang:
Teams of LLM Agents can Exploit Zero-Day Vulnerabilities. CoRR abs/2406.01637 (2024) - [i26]Richard Fang, Dylan Bowman, Daniel Kang:
Voice-Enabled AI Agents can Perform Common Scams. CoRR abs/2410.15650 (2024) - 2023
- [j12]Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 6(1): 1-52 (2023) - [j11]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. Proc. VLDB Endow. 16(11): 2897-2910 (2023) - [c12]Xiuyu Li, Yijiang Liu, Long Lian, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer:
Q-Diffusion: Quantizing Diffusion Models. ICCV 2023: 17489-17499 - [i25]Xiuyu Li, Long Lian, Yijiang Liu, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer:
Q-Diffusion: Quantizing Diffusion Models. CoRR abs/2302.04304 (2023) - [i24]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. CoRR abs/2302.05733 (2023) - [i23]Stefanos Baziotis, Daniel Kang, Charith Mendis:
Dias: Dynamic Rewriting of Pandas Code. CoRR abs/2303.16146 (2023) - [i22]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. CoRR abs/2308.09157 (2023) - [i21]Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang:
Identifying and Mitigating the Security Risks of Generative AI. CoRR abs/2308.14840 (2023) - [i20]Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang:
Removing RLHF Protections in GPT-4 via Fine-Tuning. CoRR abs/2311.05553 (2023) - 2022
- [j10]Francisco Romero, Johann Hauswald, Aditi Partap, Daniel Kang, Matei Zaharia, Christos Kozyrakis:
Optimizing Video Analytics with Declarative Model Relationships. Proc. VLDB Endow. 16(3): 447-460 (2022) - [c11]Daniel Kang, Francisco Romero, Peter D. Bailis, Christos Kozyrakis, Matei Zaharia:
VIVA: An End-to-End System for Interactive Video Analytics. CIDR 2022 - [c10]Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter D. Bailis, Matei Zaharia:
Finding Label and Model Errors in Perception Data With Learned Observation Assertions. SIGMOD Conference 2022: 496-505 - [c9]Daniel Kang, John Guibas, Peter D. Bailis, Tatsunori Hashimoto, Matei Zaharia:
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data. SIGMOD Conference 2022: 1934-1947 - [i19]Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter Bailis, Matei Zaharia:
Finding Label and Model Errors in Perception Data With Learned Observation Assertions. CoRR abs/2201.05797 (2022) - [i18]Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun:
Scaling up Trustless DNN Inference with Zero-Knowledge Proofs. CoRR abs/2210.08674 (2022) - [i17]Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun:
ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation. CoRR abs/2211.04775 (2022) - 2021
- [j9]Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone:
Network offloading policies for cloud robotics: a learning-based approach. Auton. Robots 45(7): 997-1012 (2021) - [j8]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. Proc. VLDB Endow. 14(11): 2341-2354 (2021) - [c8]Daniel Kang:
Accelerating Queries over Unstructured Data with ML. CIDR 2021 - [i16]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Proof: Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2107.12525 (2021) - [i15]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2108.06313 (2021) - 2020
- [j7]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. Proc. VLDB Endow. 13(11): 1990-2003 (2020) - [j6]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
A Demonstration of Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. Proc. VLDB Endow. 13(12): 2833-2836 (2020) - [j5]Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia:
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. Proc. VLDB Endow. 14(2): 87-100 (2020) - [c7]Daniel Kang, Tatsunori Hashimoto:
Improved Natural Language Generation via Loss Truncation. ACL 2020: 718-731 - [c6]Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia:
Model Assertions for Monitoring and Improving ML Models. MLSys 2020 - [c5]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. MLSys 2020 - [c4]Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. MLSys 2020 - [i14]Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia:
Model Assertions for Monitoring and Improving ML Models. CoRR abs/2003.01668 (2020) - [i13]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. CoRR abs/2004.00827 (2020) - [i12]Daniel Kang, Tatsunori Hashimoto:
Improved Natural Language Generation via Loss Truncation. CoRR abs/2004.14589 (2020) - [i11]Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia:
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. CoRR abs/2007.13005 (2020) - [i10]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data. CoRR abs/2009.04540 (2020)
2010 – 2019
- 2019
- [j4]Daniel Kang, Peter Bailis, Matei Zaharia:
BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics. Proc. VLDB Endow. 13(4): 533-546 (2019) - [j3]Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. ACM SIGOPS Oper. Syst. Rev. 53(1): 14-25 (2019) - [c3]Daniel Kang, Peter Bailis, Matei Zaharia:
Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine. CIDR 2019 - [c2]Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia:
LIT: Learned Intermediate Representation Training for Model Compression. ICML 2019: 3509-3518 - [c1]Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone:
Network Offloading Policies for Cloud Robotics: A Learning-Based Approach. Robotics: Science and Systems 2019 - [i9]Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone:
Network Offloading Policies for Cloud Robotics: a Learning-based Approach. CoRR abs/1902.05703 (2019) - [i8]Daniel Kang, Yi Sun, Tom Brown, Dan Hendrycks, Jacob Steinhardt:
Transfer of Adversarial Robustness Between Perturbation Types. CoRR abs/1905.01034 (2019) - [i7]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. CoRR abs/1906.01974 (2019) - [i6]Daniel Kang, Yi Sun, Dan Hendrycks, Tom Brown, Jacob Steinhardt:
Testing Robustness Against Unforeseen Adversaries. CoRR abs/1908.08016 (2019) - [i5]Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. CoRR abs/1910.01500 (2019) - 2018
- [i4]Daniel Kang, Peter Bailis, Matei Zaharia:
BlazeIt: Fast Exploratory Video Queries using Neural Networks. CoRR abs/1805.01046 (2018) - [i3]Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. CoRR abs/1806.01427 (2018) - [i2]Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia:
LIT: Block-wise Intermediate Representation Training for Model Compression. CoRR abs/1810.01937 (2018) - 2017
- [j2]Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia:
NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale. Proc. VLDB Endow. 10(11): 1586-1597 (2017) - [i1]Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia:
Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR abs/1703.02529 (2017) - 2016
- [j1]Haoyang Zeng, Tatsunori B. Hashimoto, Daniel D. Kang, David K. Gifford:
GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding. Bioinform. 32(4): 490-496 (2016)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-01-29 23:28 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
