Daniel Kang - RankMe

100 papers A* 6A 6Journal 72Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accelerating Approximate Analytical Join Queries over Unstructured Data with Statistical Guarantees. CoRR Yuxuan Zhu, Tengjun Jin, Chenghao Mo, Daniel Kang
2026	J	`jnl`	Noisy Data is Destructive to Reinforcement Learning with Verifiable Rewards. CoRR Yuxuan Zhu, Daniel Kang
2026	J	`jnl`	Pervasive Annotation Errors Break Text-to-SQL Benchmarks and Leaderboards. CoRR Tengjun Jin, Yoojin Choi, Yuxuan Zhu, Daniel Kang
2026	J	`jnl`	Pervasive Annotation Errors Break Text-to-SQL Benchmarks and Leaderboards. Proc. VLDB Endow. Tengjun Jin, Yoojin Choi, Yuxuan Zhu, Daniel Kang
2026	J	`jnl`	ReViSQL: Achieving Human-Level Text-to-SQL. CoRR Yuxuan Zhu, Tengjun Jin, Yoojin Choi, Daniel Kang
2026	J	`jnl`	SODIUM: From Open Web Data to Queryable Databases. CoRR Chuxuan Hu, Philip Li, Maxwell Yang, Daniel Kang
2026	—	`conf`	SafeSearch: Do Not Trade Safety for Utility in LLM Search Agents. EACL (Findings) Qiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, Xingzhi Guo, Daniel Kang, Joo-Kyung Kim
2026	—	`conf`	Teams of LLM Agents can Exploit Zero-Day Vulnerabilities. EACL (Volume 1: Long Papers) Yuxuan Zhu, Antony Kellermann, Akul Gupta, Philip Li, Richard Fang, Rohan Bindu, Daniel Kang
2026	A	`conf`	Text-to-SQL Benchmarks are Broken: An In-Depth Analysis of Annotation Errors. CIDR Tengjun Jin, Yoojin Choi, Yuxuan Zhu, Daniel Kang
2025	J	`jnl`	AIA Forecaster: Technical Report. CoRR 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
2025	—	`conf`	Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. NAACL (Findings) Qiusi Zhan, Richard Fang, Henil Shalin Panchal, Daniel Kang
2025	J	`jnl`	Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents. CoRR Qiusi Zhan, Richard Fang, Henil Shalin Panchal, Daniel Kang
2025	J	`jnl`	Analytical Queries for Unstructured Data. CoRR Daniel Kang
2025	J	`jnl`	Analytical Queries for Unstructured Data. Found. Trends Databases Daniel Kang
2025	J	`jnl`	Breaking Barriers: Do Reinforcement Post Training Gains Transfer To Unseen Domains? CoRR Chuxuan Hu, Yuxuan Zhu, Antony Kellermann, Caleb Biddulph, Suppakit Waiwitlikhit, Jason Benn, Daniel Kang
2025	A*	`conf`	CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities. ICML 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
2025	J	`jnl`	CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities. CoRR 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
2025	J	`jnl`	DRAMA: Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries. CoRR Chuxuan Hu, Maxwell Yang, James Weiland, Yeji Lim, Suhas Palawala, Daniel Kang
2025	J	`jnl`	ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines. CoRR Tengjun Jin, Yuxuan Zhu, Daniel Kang
2025	J	`jnl`	ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines. Proc. VLDB Endow. Tengjun Jin, Yuxuan Zhu, Daniel Kang
2025	A	`conf`	Efficient Approximate Query Processing with Block Sampling. CIDR Yuxuan Zhu, Daniel Kang
2025	J	`jnl`	Establishing Best Practices for Building Rigorous Agentic Benchmarks. CoRR 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
2025	J	`jnl`	Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation. CoRR 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
2025	J	`jnl`	LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data. CoRR Chuxuan Hu, Austin Peters, Daniel Kang
2025	J	`jnl`	Linear-time and Logarithmically-sound Permutation and Multiset SNARKs. IACR Cryptol. ePrint Arch. Bing-Jyue Chen, Lilia Tang, David Heath, Daniel Kang
2025	J	`jnl`	MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks. CoRR Hyeonjeong Ha, Qiusi Zhan, Jeonghwan Kim, Dimitrios Bralios, Saikrishna Sanniboina, Nanyun Peng, Kai-Wei Chang, Daniel Kang, Heng Ji
2025	J	`jnl`	Measuring Agents in Production. CoRR 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
2025	J	`jnl`	PandasBench: A Benchmark for the Pandas API. CoRR Alex Broihier, Stefanos Baziotis, Daniel Kang, Charith Mendis
2025	J	`jnl`	PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report). CoRR Yuxuan Zhu, Tengjun Jin, Stefanos Baziotis, Chengsong Zhang, Charith Mendis, Daniel Kang
2025	—	`conf`	REPRO-Bench: Can Agentic AI Systems Assess the Reproducibility of Social Science Research? ACL (Findings) Chuxuan Hu, Liyun Zhang, Yeji Lim, Aum Wadhwani, Austin Peters, Daniel Kang
2025	J	`jnl`	REPRO-Bench: Can Agentic AI Systems Assess the Reproducibility of Social Science Research? CoRR Chuxuan Hu, Liyun Zhang, Yeji Lim, Aum Wadhwani, Austin Peters, Daniel Kang
2025	J	`jnl`	SafeSearch: Do Not Trade Safety for Utility in LLM Search Agents. CoRR Qiusi Zhan, Angeline Budiman-Chan, Abdelrahman Zayed, Xingzhi Guo, Daniel Kang, Joo-Kyung Kim
2025	—	`conf`	UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench. ACL (1) Boxi Yu, Yuxuan Zhu, Pinjia He, Daniel Kang
2025	J	`jnl`	UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench. CoRR Boxi Yu, Yuxuan Zhu, Pinjia He, Daniel Kang
2025	J	`jnl`	Visual Backdoor Attacks on MLLM Embodied Decision Making via Contrastive Trigger Learning. CoRR Qiusi Zhan, Hyeonjeong Ha, Rui Yang, Sirui Xu, Hanyang Chen, Liang-Yan Gui, Yu-Xiong Wang, Huan Zhang, Heng Ji, Daniel Kang
2025	J	`jnl`	ZKTorch: Compiling ML Inference to Zero-Knowledge Proofs via Parallel Proof Accumulation. CoRR Bing-Jyue Chen, Lilia Tang, Daniel Kang
2024	J	`jnl`	A Safe Harbor for AI Evaluation and Red Teaming. CoRR 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
2024	—	`conf`	AIDB: a Sparsely Materialized Database for Queries using Machine Learning. DEEM@SIGMOD Tengjun Jin, Akash Mittal, Chenghao Mo, Jiahao Fang, Chengsong Zhang, Timothy Dai, Daniel Kang
2024	—	`conf`	Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. SP (Workshops) Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto
2024	—	`conf`	InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents. ACL (Findings) Qiusi Zhan, Zhixiang Liang, Zifan Ying, Daniel Kang
2024	J	`jnl`	InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents. CoRR Qiusi Zhan, Zhixiang Liang, Zifan Ying, Daniel Kang
2024	J	`jnl`	LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data. Proc. VLDB Endow. Chuxuan Hu, Austin Peters, Daniel Kang
2024	J	`jnl`	LLM Agents can Autonomously Exploit One-day Vulnerabilities. CoRR Richard Fang, Rohan Bindu, Akul Gupta, Daniel Kang
2024	J	`jnl`	LLM Agents can Autonomously Hack Websites. CoRR Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang
2024	A*	`conf`	Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 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
2024	—	`conf`	Removing RLHF Protections in GPT-4 via Fine-Tuning. NAACL (Short Papers) Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang
2024	J	`jnl`	Teams of LLM Agents can Exploit Zero-Day Vulnerabilities. CoRR Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang
2024	A*	`conf`	Trustless Audits without Revealing Data or Models. ICML Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang
2024	J	`jnl`	Trustless Audits without Revealing Data or Models. CoRR Suppakit Waiwitlikhit, Ion Stoica, Yi Sun, Tatsunori Hashimoto, Daniel Kang
2024	J	`jnl`	Voice-Enabled AI Agents can Perform Common Scams. CoRR Richard Fang, Dylan Bowman, Daniel Kang
2024	A	`conf`	ZKML: An Optimizing System for ML Inference in Zero-Knowledge Proofs. EuroSys Bing-Jyue Chen, Suppakit Waiwitlikhit, Ion Stoica, Daniel Kang
2024	—	`conf`	tailwiz: Empowering Domain Experts with Easy-to-Use, Task-Specific Natural Language Processing Models. DEEM@SIGMOD Timothy Dai, Austin Peters, Jonah B. Gelbach, David Freeman Engstrom, Daniel Kang
2023	J	`jnl`	Accelerating Aggregation Queries on Unstructured Streams of Data. CoRR Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia
2023	J	`jnl`	Accelerating Aggregation Queries on Unstructured Streams of Data. Proc. VLDB Endow. Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia
2023	J	`jnl`	Dias: Dynamic Rewriting of Pandas Code. CoRR Stefanos Baziotis, Daniel Kang, Charith Mendis
2023	J	`jnl`	Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. CoRR Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto
2023	J	`jnl`	Identifying and Mitigating the Security Risks of Generative AI. CoRR 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
2023	J	`jnl`	Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 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
2023	A*	`conf`	Q-Diffusion: Quantizing Diffusion Models. ICCV Xiuyu Li, Yijiang Liu, Long Lian, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer
2023	J	`jnl`	Q-Diffusion: Quantizing Diffusion Models. CoRR Xiuyu Li, Long Lian, Yijiang Liu, Huanrui Yang, Zhen Dong, Daniel Kang, Shanghang Zhang, Kurt Keutzer
2023	J	`jnl`	Removing RLHF Protections in GPT-4 via Fine-Tuning. CoRR Qiusi Zhan, Richard Fang, Rohan Bindu, Akul Gupta, Tatsunori Hashimoto, Daniel Kang
2022	—	`conf`	Finding Label and Model Errors in Perception Data With Learned Observation Assertions. SIGMOD Conference Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter D. Bailis, Matei Zaharia
2022	J	`jnl`	Finding Label and Model Errors in Perception Data With Learned Observation Assertions. CoRR Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter Bailis, Matei Zaharia
2022	J	`jnl`	Optimizing Video Analytics with Declarative Model Relationships. Proc. VLDB Endow. Francisco Romero, Johann Hauswald, Aditi Partap, Daniel Kang, Matei Zaharia, Christos Kozyrakis
2022	J	`jnl`	Scaling up Trustless DNN Inference with Zero-Knowledge Proofs. CoRR Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun
2022	—	`conf`	TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data. SIGMOD Conference Daniel Kang, John Guibas, Peter D. Bailis, Tatsunori Hashimoto, Matei Zaharia
2022	A	`conf`	VIVA: An End-to-End System for Interactive Video Analytics. CIDR Daniel Kang, Francisco Romero, Peter D. Bailis, Christos Kozyrakis, Matei Zaharia
2022	J	`jnl`	ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation. CoRR Daniel Kang, Tatsunori Hashimoto, Ion Stoica, Yi Sun
2021	J	`jnl`	Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia
2021	J	`jnl`	Accelerating Approximate Aggregation Queries with Expensive Predicates. Proc. VLDB Endow. Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia
2021	A	`conf`	Accelerating Queries over Unstructured Data with ML. CIDR Daniel Kang
2021	J	`jnl`	Network offloading policies for cloud robotics: a learning-based approach. Auton. Robots Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2021	J	`jnl`	Proof: Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia
2020	J	`jnl`	A Demonstration of Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. Proc. VLDB Endow. Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia
2020	J	`jnl`	Approximate Selection with Guarantees using Proxies. CoRR Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia
2020	J	`jnl`	Approximate Selection with Guarantees using Proxies. Proc. VLDB Endow. Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia
2020	A*	`conf`	Improved Natural Language Generation via Loss Truncation. ACL Daniel Kang, Tatsunori Hashimoto
2020	J	`jnl`	Improved Natural Language Generation via Loss Truncation. CoRR Daniel Kang, Tatsunori Hashimoto
2020	J	`jnl`	Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. CoRR Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia
2020	J	`jnl`	Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. Proc. VLDB Endow. Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia
2020	—	`conf`	MLPerf Training Benchmark. MLSys 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
2020	—	`conf`	Model Assertions for Monitoring and Improving ML Models. MLSys Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia
2020	J	`jnl`	Model Assertions for Monitoring and Improving ML Models. CoRR Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia
2020	J	`jnl`	Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data. CoRR Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia
2020	—	`conf`	Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. MLSys Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia
2019	J	`jnl`	Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. ACM SIGOPS Oper. Syst. Rev. Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia
2019	J	`jnl`	BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics. Proc. VLDB Endow. Daniel Kang, Peter Bailis, Matei Zaharia
2019	A	`conf`	Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine. CIDR Daniel Kang, Peter Bailis, Matei Zaharia
2019	A*	`conf`	LIT: Learned Intermediate Representation Training for Model Compression. ICML Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia
2019	J	`jnl`	MLPerf Training Benchmark. CoRR 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
2019	—	`conf`	Network Offloading Policies for Cloud Robotics: A Learning-Based Approach. Robotics: Science and Systems Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2019	J	`jnl`	Network Offloading Policies for Cloud Robotics: a Learning-based Approach. CoRR Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2019	J	`jnl`	Testing Robustness Against Unforeseen Adversaries. CoRR Daniel Kang, Yi Sun, Dan Hendrycks, Tom Brown, Jacob Steinhardt
2019	J	`jnl`	Transfer of Adversarial Robustness Between Perturbation Types. CoRR Daniel Kang, Yi Sun, Tom Brown, Dan Hendrycks, Jacob Steinhardt
2019	J	`jnl`	Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. CoRR Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia
2018	J	`jnl`	Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. CoRR Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia
2018	J	`jnl`	BlazeIt: Fast Exploratory Video Queries using Neural Networks. CoRR Daniel Kang, Peter Bailis, Matei Zaharia
2018	J	`jnl`	LIT: Block-wise Intermediate Representation Training for Model Compression. CoRR Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia
2017	J	`jnl`	NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale. Proc. VLDB Endow. Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia
2017	J	`jnl`	Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia