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ORCIDJoseph Gonzalez 0001
Joseph E. Gonzalez
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- affiliation: University of California at Berkeley, CA, USA
- affiliation (former): Carnegie Mellon University, Santa Clara, CA, USA
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2020 – today
- 2021
[i86]Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. CoRR abs/2103.02145 (2021)- 2020
- [j11]Joseph Gonzalez:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 43(2): 2-3 (2020) - [j10]David E. Culler, Prabal Dutta, Gabe Fierro, Joseph E. Gonzalez, Nathan Pemberton, Johann Schleier-Smith, Kalyanaraman Shankari, Alvin Wan, Thomas Zachariah:
CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing. IEEE Data Eng. Bull. 43(2): 83-94 (2020) - [j9]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. Proc. VLDB Endow. 13(11): 2033-2046 (2020) - [j8]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Joseph Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. Proc. VLDB Endow. 13(11): 2438-2452 (2020) - [j7]Brijen Thananjeyan
, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg:
Safety Augmented Value Estimation From Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks. IEEE Robotics Autom. Lett. 5(2): 3612-3619 (2020) - [j6]Ajay Kumar Tanwani, Raghav Anand, Joseph E. Gonzalez, Ken Goldberg:
RILaaS: Robot Inference and Learning as a Service. IEEE Robotics Autom. Lett. 5(3): 4423-4430 (2020) - [c56]Vidit Saxena, Joakim Jaldén, Joseph Gonzalez:
Thompson Sampling for Linearly Constrained Bandits. AISTATS 2020: 1999-2009 - [c55]Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov:
InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC 2020: 477-491 - [c54]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CVPR 2020: 12962-12971 - [c53]Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez, Joseph M. Hellerstein, Jose M. Faleiro:
A fault-tolerance shim for serverless computing. EuroSys 2020: 15:1-15:15 - [c52]Ankur Dave, Chester Leung, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Oblivious coopetitive analytics using hardware enclaves. EuroSys 2020: 39:1-39:17 - [c51]Xiayue Charles Lin, Joseph E. Gonzalez, Joseph M. Hellerstein:
Serverless Boom or Bust? An Analysis of Economic Incentives. HotCloud 2020 - [c50]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. ICML 2020: 8253-8265 - [c49]Xin Wang, Thomas E. Huang, Joseph Gonzalez, Trevor Darrell, Fisher Yu:
Frustratingly Simple Few-Shot Object Detection. ICML 2020: 9919-9928 - [c48]Jeffrey Ichnowski, William Lee, Victor Murta, Samuel Paradis, Ron Alterovitz, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg:
Fog Robotics Algorithms for Distributed Motion Planning Using Lambda Serverless Computing. ICRA 2020: 4232-4238 - [c47]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg:
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data. ICRA 2020: 9411-9418 - [c46]Samvit Jain, Xun Zhang, Yuhao Zhou, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Paramvir Bahl, Joseph Gonzalez:
Spatula: Efficient cross-camera video analytics on large camera networks. SEC 2020: 110-124 - [c45]Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph Gonzalez:
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. MLSys 2020 - [c44]Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez:
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. NeurIPS 2020 - [c43]Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Boundary thickness and robustness in learning models. NeurIPS 2020 - [c42]Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica:
Ansor: Generating High-Performance Tensor Programs for Deep Learning. OSDI 2020: 863-879 - [i85]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. CoRR abs/2001.00888 (2020) - [i84]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. CoRR abs/2001.02338 (2020) - [i83]Vikram Sreekanti, Chenggang Wu, Xiayue Charles Lin, Johann Schleier-Smith, Jose M. Faleiro, Joseph E. Gonzalez, Joseph M. Hellerstein, Alexey Tumanov:
Cloudburst: Stateful Functions-as-a-Service. CoRR abs/2001.04592 (2020) - [i82]Bohan Zhai, Tianren Gao, Flora Xue, Daniel Rothchild, Bichen Wu, Joseph E. Gonzalez, Kurt Keutzer:
SqueezeWave: Extremely Lightweight Vocoders for On-device Speech Synthesis. CoRR abs/2001.05685 (2020) - [i81]Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez:
Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. CoRR abs/2002.11794 (2020) - [i80]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Joseph E. Gonzalez, Aaron D. Ames, Ken Goldberg:
ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions. CoRR abs/2003.01410 (2020) - [i79]Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg:
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data. CoRR abs/2003.01835 (2020) - [i78]Vikram Sreekanti, Chenggang Wu, Saurav Chhatrapati, Joseph E. Gonzalez, Joseph M. Hellerstein, Jose M. Faleiro:
A Fault-Tolerance Shim for Serverless Computing. CoRR abs/2003.06007 (2020) - [i77]Xin Wang, Thomas E. Huang, Trevor Darrell, Joseph E. Gonzalez, Fisher Yu:
Frustratingly Simple Few-Shot Object Detection. CoRR abs/2003.06957 (2020) - [i76]Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Jennifer Grannen, Minho Hwang, Ryan Hoque, Joseph E. Gonzalez, Nawid Jamali, Katsu Yamane, Soshi Iba, Ken Goldberg:
Learning to Smooth and Fold Real Fabric Using Dense Object Descriptors Trained on Synthetic Color Images. CoRR abs/2003.12698 (2020) - [i75]Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez:
NBDT: Neural-Backed Decision Trees. CoRR abs/2004.00221 (2020) - [i74]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CoRR abs/2004.05565 (2020) - [i73]Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Mechanism Design with Bandit Feedback. CoRR abs/2004.08924 (2020) - [i72]Vidit Saxena, Joseph E. Gonzalez, Joakim Jaldén:
Thompson Sampling for Linearly Constrained Bandits. CoRR abs/2004.09258 (2020) - [i71]David E. Culler, Prabal Dutta, Gabe Fierro, Joseph E. Gonzalez, Nathan Pemberton, Johann Schleier-Smith, Kalyanaraman Shankari, Alvin Wan, Thomas Zachariah:
CoVista: A Unified View on Privacy Sensitive Mobile Contact Tracing Effort. CoRR abs/2005.13164 (2020) - [i70]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function. CoRR abs/2006.02049 (2020) - [i69]Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica:
Ansor : Generating High-Performance Tensor Programs for Deep Learning. CoRR abs/2006.06762 (2020) - [i68]Alvin Wan, Daniel Ho, Younjin Song, Henk Tillman, Sarah Adel Bargal, Joseph E. Gonzalez:
SegNBDT: Visual Decision Rules for Segmentation. CoRR abs/2006.06868 (2020) - [i67]Rolando Garcia, Eric Liu, Vikram Sreekanti, Bobby Yan, Anusha Dandamudi, Joseph E. Gonzalez, Joseph M. Hellerstein, Koushik Sen:
Hindsight Logging for Model Training. CoRR abs/2006.07357 (2020) - [i66]Mong H. Ng, Kaahan Radia, Jianfei Chen, Dequan Wang, Ionel Gog, Joseph E. Gonzalez:
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud. CoRR abs/2006.11436 (2020) - [i65]Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica:
Contrastive Code Representation Learning. CoRR abs/2007.04973 (2020) - [i64]Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney:
Boundary thickness and robustness in learning models. CoRR abs/2007.05086 (2020) - [i63]Vikram Sreekanti, Harikaran Subbaraj, Chenggang Wu, Joseph E. Gonzalez, Joseph M. Hellerstein:
Optimizing Prediction Serving on Low-Latency Serverless Dataflow. CoRR abs/2007.05832 (2020) - [i62]Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora:
FetchSGD: Communication-Efficient Federated Learning with Sketching. CoRR abs/2007.07682 (2020) - [i61]Zhengming Zhang, Zhewei Yao, Yaoqing Yang, Yujun Yan, Joseph E. Gonzalez, Michael W. Mahoney:
Benchmarking Semi-supervised Federated Learning. CoRR abs/2008.11364 (2020) - [i60]Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E. Gonzalez, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, Kurt Keutzer:
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation. CoRR abs/2009.00155 (2020) - [i59]Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell:
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting. CoRR abs/2010.01528 (2020) - [i58]Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Ryan Hoque, Joseph E. Gonzalez, Ken Goldberg:
MMGSD: Multi-Modal Gaussian Shape Descriptors for Correspondence Matching in 1D and 2D Deformable Objects. CoRR abs/2010.04339 (2020) - [i57]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
Multi-Agent Collaboration via Reward Attribution Decomposition. CoRR abs/2010.08531 (2020) - [i56]Jianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez:
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. CoRR abs/2010.14298 (2020) - [i55]Brijen Thananjeyan, Ashwin Balakrishna, Suraj Nair, Michael Luo, Krishnan Srinivasan, Minho Hwang, Joseph E. Gonzalez, Julian Ibarz, Chelsea Finn, Ken Goldberg:
Recovery RL: Safe Reinforcement Learning with Learned Recovery Zones. CoRR abs/2010.15920 (2020) - [i54]Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez:
Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism. CoRR abs/2011.00330 (2020) - [i53]Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Minho Hwang, Vainavi Viswanath, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg:
Untangling Dense Knots by Learning Task-Relevant Keypoints. CoRR abs/2011.04999 (2020) - [i52]Samuel Paradis, Minho Hwang, Brijen Thananjeyan, Jeffrey Ichnowski, Daniel Seita, Danyal Fer, Thomas Low, Joseph E. Gonzalez, Ken Goldberg:
Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation. CoRR abs/2011.06163 (2020) - [i51]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
BeBold: Exploration Beyond the Boundary of Explored Regions. CoRR abs/2012.08621 (2020) - [i50]Kirthevasan Kandasamy, Gur-Eyal Sela, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica:
Online Learning Demands in Max-min Fairness. CoRR abs/2012.08648 (2020)
2010 – 2019
- 2019
- [c41]Joseph M. Hellerstein, Jose M. Faleiro, Joseph Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CIDR 2019 - [c40]Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline. SoCC 2019: 61-73 - [c39]Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Felix Li, Arsh Zahed, Joseph E. Gonzalez, Ken Goldberg:
On-Policy Robot Imitation Learning from a Converging Supervisor. CoRL 2019: 24-41 - [c38]Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez:
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning. CVPR 2019: 1831-1840 - [c37]Samvit Jain, Xin Wang, Joseph E. Gonzalez:
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video. CVPR 2019: 8866-8875 - [c36]Zuxuan Wu, Xin Wang, Joseph Gonzalez, Tom Goldstein, Larry Davis:
ACE: Adapting to Changing Environments for Semantic Segmentation. ICCV 2019: 2121-2130 - [c35]Ajay Kumar Tanwani, Nitesh Mor, John Kubiatowicz, Joseph E. Gonzalez, Ken Goldberg:
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering. ICRA 2019: 4559-4566 - [c34]Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros:
ANODEV2: A Coupled Neural ODE Framework. NeurIPS 2019: 5152-5162 - [c33]Vidit Saxena, Joakim Jaldén, Joseph E. Gonzalez, Mats Bengtsson, Hugo M. Tullberg, Ion Stoica:
Contextual Multi-Armed Bandits for Link Adaptation in Cellular Networks. NetAI@SIGCOMM 2019: 44-49 - [c32]Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Helen: Maliciously Secure Coopetitive Learning for Linear Models. IEEE Symposium on Security and Privacy 2019: 724-738 - [c31]Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. UAI 2019: 552-562 - [c30]Samvit Jain, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Joseph Gonzalez:
Scaling Video Analytics Systems to Large Camera Deployments. HotMobile 2019: 9-14 - [i49]Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica:
Dynamic Space-Time Scheduling for GPU Inference. CoRR abs/1901.00041 (2019) - [i48]Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica:
The OoO VLIW JIT Compiler for GPU Inference. CoRR abs/1901.10008 (2019) - [i47]Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, Joao Carreira, Karl Krauth, Neeraja Jayant Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson:
Cloud Programming Simplified: A Berkeley View on Serverless Computing. CoRR abs/1902.03383 (2019) - [i46]Vidit Saxena, Joakim Jaldén, Joseph E. Gonzalez, Ion Stoica, Hugo M. Tullberg:
Constrained Thompson Sampling for Wireless Link Optimization. CoRR abs/1902.11102 (2019) - [i45]Ajay Kumar Tanwani, Nitesh Mor, John Kubiatowicz, Joseph E. Gonzalez, Ken Goldberg:
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering. CoRR abs/1903.09589 (2019) - [i44]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i43]Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez:
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning. CoRR abs/1904.05967 (2019) - [i42]Zuxuan Wu, Xin Wang, Joseph E. Gonzalez, Tom Goldstein, Larry S. Davis:
ACE: Adapting to Changing Environments for Semantic Segmentation. CoRR abs/1904.06268 (2019) - [i41]Brijen Thananjeyan, Ashwin Balakrishna, Ugo Rosolia, Felix Li, Rowan McAllister, Joseph E. Gonzalez, Sergey Levine, Francesco Borrelli, Ken Goldberg:
Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations. CoRR abs/1905.13402 (2019) - [i40]Tianjun Zhang, Zhewei Yao, Amir Gholami, Kurt Keutzer, Joseph Gonzalez, George Biros, Michael W. Mahoney:
ANODEV2: A Coupled Neural ODE Evolution Framework. CoRR abs/1906.04596 (2019) - [i39]Xin Wang, Fisher Yu, Trevor Darrell, Joseph E. Gonzalez:
Task-Aware Deep Sampling for Feature Generation. CoRR abs/1906.04854 (2019) - [i38]Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken Goldberg:
On-Policy Robot Imitation Learning from a Converging Supervisor. CoRR abs/1907.03423 (2019) - [i37]Wenting Zheng, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Helen: Maliciously Secure Coopetitive Learning for Linear Models. CoRR abs/1907.07212 (2019) - [i36]Ameer Haj-Ali, Nesreen K. Ahmed, Theodore L. Willke, Joseph Gonzalez, Krste Asanovic, Ion Stoica:
Deep Reinforcement Learning in System Optimization. CoRR abs/1908.01275 (2019) - [i35]Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez:
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization. CoRR abs/1910.02653 (2019) - [i34]Tianyuan Zhang, Bichen Wu, Xin Wang, Joseph Gonzalez, Kurt Keutzer:
Domain-Aware Dynamic Networks. CoRR abs/1911.13237 (2019) - 2018
- [j5]Daniel Crankshaw, Joseph Gonzalez, Peter Bailis:
Research for practice: prediction-serving systems. Commun. ACM 61(8): 45-49 (2018) - [j4]Joseph E. Gonzalez:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 41(4): 4 (2018) - [c29]Bichen Wu, Alvin Wan, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer:
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions. CVPR 2018: 9127-9135 - [c28]Samvit Jain, Joseph E. Gonzalez:
Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation. ECCV Workshops (4) 2018: 3-6 - [c27]Xin Wang, Fisher Yu, Zi-Yi Dou, Trevor Darrell, Joseph E. Gonzalez:
SkipNet: Learning Dynamic Routing in Convolutional Networks. ECCV (13) 2018: 420-436 - [c26]Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Ken Goldberg, Joseph Gonzalez, Michael I. Jordan, Ion Stoica:
RLlib: Abstractions for Distributed Reinforcement Learning. ICML 2018: 3059-3068 - [c25]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. UAI 2018: 580-590 - [i33]Vladimir Feinberg, Alvin Wan, Ion Stoica, Michael I. Jordan, Joseph E. Gonzalez, Sergey Levine:
Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning. CoRR abs/1803.00101 (2018) - [i32]Samvit Jain, Joseph E. Gonzalez:
Fast Semantic Segmentation on Video Using Motion Vector-Based Feature Interpolation. CoRR abs/1803.07742 (2018) - [i31]Sicheng Zhao, Bichen Wu, Joseph Gonzalez, Sanjit A. Seshia, Kurt Keutzer:
Unsupervised Domain Adaptation: from Simulation Engine to the RealWorld. CoRR abs/1803.09180 (2018) - [i30]Xin Wang, Fisher Yu, Ruth Wang, Yi-An Ma, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. CoRR abs/1806.01531 (2018) - [i29]Richard Liaw, Eric Liang, Robert Nishihara, Philipp Moritz, Joseph E. Gonzalez, Ion Stoica:
Tune: A Research Platform for Distributed Model Selection and Training. CoRR abs/1807.05118 (2018) - [i28]Samvit Jain, Xin Wang, Joseph Gonzalez:
Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video. CoRR abs/1807.06667 (2018) - [i27]Samvit Jain, Ganesh Ananthanarayanan, Junchen Jiang, Yuanchao Shu, Joseph E. Gonzalez:
Scaling Video Analytics Systems to Large Camera Deployments. CoRR abs/1809.02318 (2018) - [i26]Samvit Jain, Joseph E. Gonzalez:
Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video. CoRR abs/1810.04047 (2018) - [i25]Samvit Jain, Junchen Jiang, Yuanchao Shu, Ganesh Ananthanarayanan, Joseph Gonzalez:
ReXCam: Resource-Efficient, Cross-Camera Video Analytics at Enterprise Scale. CoRR abs/1811.01268 (2018) - [i24]Noah Golmant, Nikita Vemuri, Zhewei Yao, Vladimir Feinberg, Amir Gholami, Kai Rothauge, Michael W. Mahoney, Joseph Gonzalez:
On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent. CoRR abs/1811.12941 (2018) - [i23]J. Weston Hughes, Taylor Sittler, Anthony D. Joseph, Jeffrey E. Olgin, Joseph E. Gonzalez, Geoffrey H. Tison:
Using Multitask Learning to Improve 12-Lead Electrocardiogram Classification. CoRR abs/1812.00497 (2018) - [i22]Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov:
InferLine: ML Inference Pipeline Composition Framework. CoRR abs/1812.01776 (2018) - [i21]Joseph M. Hellerstein, Jose M. Faleiro, Joseph E. Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu:
Serverless Computing: One Step Forward, Two Steps Back. CoRR abs/1812.03651 (2018) - 2017
- [c24]Francois Belletti, Evan R. Sparks, Alexandre M. Bayen, Joseph Gonzalez:
Random projection design for scalable implicit smoothing of randomly observed stochastic processes. AISTATS 2017: 700-708 - [c23]Joseph M. Hellerstein, Vikram Sreekanti, Joseph E. Gonzalez, James Dalton, Akon Dey, Sreyashi Nag, Krishna Ramachandran, Sudhanshu Arora, Arka Bhattacharyya, Shirshanka Das, Mark Donsky, Gabriel Fierro, Chang She, Carl Steinbach, Venkat Subramanian, Eric Sun:
Ground: A Data Context Service. CIDR 2017 - [c22]Neeraja Jayant Yadwadkar, Bharath Hariharan, Joseph E. Gonzalez, Burton Smith, Randy H. Katz:
Selecting the best VM across multiple public clouds: a data-driven performance modeling approach. SoCC 2017: 452-465 - [c21]Wenting Zheng, Ankur Dave, Jethro G. Beekman, Raluca Ada Popa, Joseph E. Gonzalez, Ion Stoica:
Opaque: An Oblivious and Encrypted Distributed Analytics Platform. NSDI 2017: 283-298 - [c20]Daniel Crankshaw, Xin Wang, Giulio Zhou, Michael J. Franklin, Joseph E. Gonzalez, Ion Stoica:
Clipper: A Low-Latency Online Prediction Serving System. NSDI 2017: 613-627 - [i20]Xinghao Pan, Shivaram Venkataraman, Zizheng Tai, Joseph Gonzalez:
Hemingway: Modeling Distributed Optimization Algorithms. CoRR abs/1702.05865 (2017) - [i19]Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Joseph E. Gonzalez:
IDK Cascades: Fast Deep Learning by Learning not to Overthink. CoRR abs/1706.00885 (2017) - [i18]Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg:
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. CoRR abs/1711.01503 (2017) - [i17]Bichen Wu, Alvin Wan, Xiangyu Yue, Peter H. Jin, Sicheng Zhao, Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer:
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions. CoRR abs/1711.08141 (2017) - [i16]Xin Wang, Fisher Yu, Zi-Yi Dou, Joseph E. Gonzalez:
SkipNet: Learning Dynamic Routing in Convolutional Networks. CoRR abs/1711.09485 (2017) - [i15]Ion Stoica, Dawn Song, Raluca Ada Popa, David A. Patterson, Michael W. Mahoney, Randy H. Katz, Anthony D. Joseph, Michael I. Jordan, Joseph M. Hellerstein, Joseph E. Gonzalez, Ken Goldberg, Ali Ghodsi, David E. Culler, Pieter Abbeel:
A Berkeley View of Systems Challenges for AI. CoRR abs/1712.05855 (2017) - [i14]Eric Liang, Richard Liaw, Robert Nishihara, Philipp Moritz, Roy Fox, Joseph Gonzalez, Ken Goldberg,