Stop the war!Остановите войну!
for scientists:
Google
Google Scholar
Semantic Scholar
IA Scholar
CiteSeerX
ORCIDStuart Russell 0001
Stuart J. Russell
Person information
- affiliation: University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2022
[c143]Stuart Russell:
Provably Beneficial Artificial Intelligence. IUI 2022: 3- [i65]Joar Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, Adam Gleave:
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. CoRR abs/2203.07475 (2022) - [i64]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. CoRR abs/2204.11966 (2022) - [i63]Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. CoRR abs/2205.07886 (2022) - 2021
- [c142]Prasad Tadepalli, Stuart J. Russell:
PAC Learning of Causal Trees with Latent Variables. AAAI 2021: 9774-9781 - [c141]Charlotte Roman, Michael Dennis, Andrew Critch, Stuart Russell:
Accumulating Risk Capital Through Investing in Cooperation. AAMAS 2021: 1073-1081 - [c140]Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike:
Quantifying Differences in Reward Functions. ICLR 2021 - [c139]Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah:
An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks 2021 - [c138]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS 2021: 9663-9680 - [c137]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. NeurIPS 2021: 11702-11716 - [c136]Cassidy Laidlaw, Stuart Russell:
Uncertain Decisions Facilitate Better Preference Learning. NeurIPS 2021: 15070-15083 - [c135]Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart J. Russell, Noam Brown:
Scalable Online Planning via Reinforcement Learning Fine-Tuning. NeurIPS 2021: 16951-16963 - [c134]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Preference Shift in Recommender Systems. RecSys 2021: 661-667 - [p4]Raja Chatila, Virginia Dignum, Michael Fisher
, Fosca Giannotti, Katharina Morik, Stuart Russell, Karen Yeung:
Trustworthy AI. Reflections on Artificial Intelligence for Humanity 2021: 13-39 - [p3]Jocelyn Maclure, Stuart Russell:
AI for Humanity: The Global Challenges. Reflections on Artificial Intelligence for Humanity 2021: 116-126 - [i62]Charlotte Roman, Michael Dennis, Andrew Critch, Stuart Russell:
Accumulating Risk Capital Through Investing in Cooperation. CoRR abs/2101.10305 (2021) - [i61]Daniel Filan, Stephen Casper, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell:
Clusterability in Neural Networks. CoRR abs/2103.03386 (2021) - [i60]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. CoRR abs/2103.12021 (2021) - [i59]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. CoRR abs/2106.10268 (2021) - [i58]Cassidy Laidlaw, Stuart Russell:
Learning the Preferences of Uncertain Humans with Inverse Decision Theory. CoRR abs/2106.10394 (2021) - [i57]Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan:
The MineRL BASALT Competition on Learning from Human Feedback. CoRR abs/2107.01969 (2021) - [i56]Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine:
Explore and Control with Adversarial Surprise. CoRR abs/2107.07394 (2021) - [i55]Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart Russell, Noam Brown:
Scalable Online Planning via Reinforcement Learning Fine-Tuning. CoRR abs/2109.15316 (2021) - [i54]Arnaud Fickinger, Samuel Cohen, Stuart Russell, Brandon Amos:
Cross-Domain Imitation Learning via Optimal Transport. CoRR abs/2110.03684 (2021) - [i53]Shlomi Hod, Stephen Casper, Daniel Filan, Cody Wild, Andrew Critch, Stuart Russell:
Detecting Modularity in Deep Neural Networks. CoRR abs/2110.08058 (2021) - 2020
- [b6]Stuart Russell, Peter Norvig:
Artificial Intelligence: A Modern Approach (4th Edition). Pearson 2020, ISBN 9780134610993 - [c133]Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell:
Adversarial Policies: Attacking Deep Reinforcement Learning. ICLR 2020 - [c132]Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine:
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. NeurIPS 2020 - [c131]Paria Rashidinejad, Jiantao Jiao, Stuart Russell:
SLIP: Learning to predict in unknown dynamical systems with long-term memory. NeurIPS 2020 - [c130]Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell:
The MAGICAL Benchmark for Robust Imitation. NeurIPS 2020 - [i52]Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell:
Neural Networks are Surprisingly Modular. CoRR abs/2003.04881 (2020) - [i51]Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike:
Quantifying Differences in Reward Functions. CoRR abs/2006.13900 (2020) - [i50]Arnaud Fickinger, Simon Zhuang, Dylan Hadfield-Menell, Stuart Russell:
Multi-Principal Assistance Games. CoRR abs/2007.09540 (2020) - [i49]Paria Rashidinejad, Jiantao Jiao, Stuart Russell:
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory. CoRR abs/2010.05899 (2020) - [i48]Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell:
The MAGICAL Benchmark for Robust Imitation. CoRR abs/2011.00401 (2020) - [i47]Pedro Freire, Adam Gleave, Sam Toyer, Stuart Russell:
DERAIL: Diagnostic Environments for Reward And Imitation Learning. CoRR abs/2012.01365 (2020) - [i46]Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine:
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. CoRR abs/2012.02096 (2020) - [i45]Eric J. Michaud, Adam Gleave, Stuart Russell:
Understanding Learned Reward Functions. CoRR abs/2012.05862 (2020) - [i44]Arnaud Fickinger, Simon Zhuang, Andrew Critch, Dylan Hadfield-Menell, Stuart Russell:
Multi-Principal Assistance Games: Definition and Collegial Mechanisms. CoRR abs/2012.14536 (2020)
2010 – 2019
- 2019
- [c129]Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, Stuart Russell:
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient. AAAI 2019: 4213-4220 - [c128]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Bayesian Relational Memory for Semantic Visual Navigation. ICCV 2019: 2769-2779 - [c127]David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Stuart J. Russell, Thomas L. Griffiths:
Cognitive model priors for predicting human decisions. ICML 2019: 5133-5141 - [i43]Ori Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell, Evan C. Carter, James F. Cavanagh, Ido Erev:
Predicting human decisions with behavioral theories and machine learning. CoRR abs/1904.06866 (2019) - [i42]David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell:
Cognitive Model Priors for Predicting Human Decisions. CoRR abs/1905.09397 (2019) - [i41]Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, Stuart Russell:
Adversarial Policies: Attacking Deep Reinforcement Learning. CoRR abs/1905.10615 (2019) - [i40]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Bayesian Relational Memory for Semantic Visual Navigation. CoRR abs/1909.04306 (2019) - 2018
- [c126]Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. ICML 2018: 3391-3399 - [c125]Yi Wu, Siddharth Srivastava, Nicholas Hay, Simon S. Du, Stuart Russell:
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms. ICML 2018: 5339-5348 - [c124]Tongzhou Wang, Yi Wu, Dave Moore, Stuart J. Russell:
Meta-Learning MCMC Proposals. NeurIPS 2018: 4150-4160 - [c123]Nishant Desai, Andrew Critch, Stuart J. Russell:
Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making. NeurIPS 2018: 4717-4725 - [c122]Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart J. Russell, Pieter Abbeel:
Learning Plannable Representations with Causal InfoGAN. NeurIPS 2018: 8747-8758 - [i39]Yi Wu, Siddharth Srivastava, Nicholas Hay, Simon S. Du, Stuart Russell:
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms. CoRR abs/1806.02027 (2018) - [i38]Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. CoRR abs/1806.03820 (2018) - [i37]Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel:
Learning Plannable Representations with Causal InfoGAN. CoRR abs/1807.09341 (2018) - [i36]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Learning and Planning with a Semantic Model. CoRR abs/1809.10842 (2018) - [i35]Aaron Tucker, Adam Gleave, Stuart Russell:
Inverse reinforcement learning for video games. CoRR abs/1810.10593 (2018) - 2017
- [c121]Yusuf Bugra Erol, Yi Wu, Lei Li, Stuart Russell:
A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models. AAAI 2017: 1861-1869 - [c120]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. AAAI Workshops 2017 - [c119]David A. Moore, Stuart Russell:
Signal-based Bayesian Seismic Monitoring. AISTATS 2017: 1293-1301 - [c118]Yi Wu, David Bamman, Stuart Russell:
Adversarial Training for Relation Extraction. EMNLP 2017: 1778-1783 - [c117]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. IJCAI 2017: 220-227 - [c116]Aijun Bai, Stuart Russell:
Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions. IJCAI 2017: 1418-1424 - [c115]Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell:
Should Robots be Obedient? IJCAI 2017: 4754-4760 - [c114]Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart J. Russell, Anca D. Dragan:
Inverse Reward Design. NIPS 2017: 6765-6774 - [c113]Aijun Bai, Stuart Russell, Xiaoping Chen:
Concurrent Hierarchical Reinforcement Learning for RoboCup Keepaway. RoboCup 2017: 190-203 - [i34]David A. Moore, Stuart J. Russell:
Signal-based Bayesian Seismic Monitoring. CoRR abs/1703.00561 (2017) - [i33]Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell:
Should Robots be Obedient? CoRR abs/1705.09990 (2017) - [i32]Tongzhou Wang, Yi Wu, David A. Moore, Stuart J. Russell:
Neural Block Sampling. CoRR abs/1708.06040 (2017) - [i31]Andrew Critch, Stuart Russell:
Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making. CoRR abs/1711.00363 (2017) - [i30]Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart Russell, Anca D. Dragan:
Inverse Reward Design. CoRR abs/1711.02827 (2017) - 2016
- [c112]Siddharth Srivastava, Stuart Russell, Alessandro Pinto:
Metaphysics of Planning Domain Descriptions. AAAI 2016: 1074-1080 - [c111]Stuart Russell, Ole Torp Lassen, Justin Uang, Wei Wang:
The Physics of Text: Ontological Realism in Information Extraction. AKBC@NAACL-HLT 2016: 51-56 - [c110]Aijun Bai, Siddharth Srivastava, Stuart Russell:
Markovian State and Action Abstractions for MDPs via Hierarchical MCTS. IJCAI 2016: 3029-3039 - [c109]Yi Wu, Lei Li, Stuart Russell, Rastislav Bodík:
Swift: Compiled Inference for Probabilistic Programming Languages. IJCAI 2016: 3637-3645 - [c108]Dylan Hadfield-Menell, Christopher Lin, Rohan Chitnis, Stuart Russell, Pieter Abbeel:
Sequential quadratic programming for task plan optimization. IROS 2016: 5040-5047 - [c107]Dylan Hadfield-Menell, Stuart Russell, Pieter Abbeel, Anca D. Dragan:
Cooperative Inverse Reinforcement Learning. NIPS 2016: 3909-3917 - [e2]Blai Bonet, Sven Koenig, Benjamin Kuipers, Illah R. Nourbakhsh, Stuart Russell, Moshe Y. Vardi, Toby Walsh:
AI, Ethics, and Society, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 13, 2016. AAAI Technical Report WS-16-02, AAAI Press 2016 [contents] - [i29]Stuart Russell, Daniel Dewey, Max Tegmark:
Research Priorities for Robust and Beneficial Artificial Intelligence. CoRR abs/1602.03506 (2016) - [i28]Yusuf Bugra Erol, Yi Wu, Lei Li, Stuart Russell:
Towards Practical Bayesian Parameter and State Estimation. CoRR abs/1603.08988 (2016) - [i27]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
Cooperative Inverse Reinforcement Learning. CoRR abs/1606.03137 (2016) - [i26]Yi Wu, Lei Li, Stuart Russell, Rastislav Bodík:
Swift: Compiled Inference for Probabilistic Programming Languages. CoRR abs/1606.09242 (2016) - [i25]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. CoRR abs/1611.08219 (2016) - 2015
- [j18]Stuart Russell, Tom Dietterich, Eric Horvitz, Bart Selman, Francesca Rossi, Demis Hassabis, Shane Legg, Mustafa Suleyman, Dileep George, D. Scott Phoenix:
Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter. AI Mag. 36(4): 3-4 (2015) - [j17]Stuart Russell, Daniel Dewey, Max Tegmark:
Research Priorities for Robust and Beneficial Artificial Intelligence. AI Mag. 36(4): 105-114 (2015) - [j16]Eric Eaton, Tom Dietterich, Maria L. Gini, Barbara J. Grosz, Charles L. Isbell Jr., Subbarao Kambhampati, Michael L. Littman, Francesca Rossi, Stuart Russell, Peter Stone, Toby Walsh, Michael J. Wooldridge:
Who speaks for AI? AI Matters 2(2): 4-14 (2015) - [j15]Stuart Russell:
Unifying logic and probability. Commun. ACM 58(7): 88-97 (2015) - [c106]Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell:
Tractability of Planning with Loops. AAAI 2015: 3393-3401 - [c105]Siddharth Srivastava, Stuart Russell, Alessandro Pinto:
Metaphysics of Planning Domain Descriptions. AAAI Fall Symposia 2015: 83-90 - [c104]David A. Moore, Stuart J. Russell:
Gaussian Process Random Fields. NIPS 2015: 3357-3365 - [c103]Dylan Hadfield-Menell, Stuart Russell:
Multitasking: Optimal Planning for Bandit Superprocesses. UAI 2015: 345-354 - [c102]Wei Wang, Stuart Russell:
A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC. UAI 2015: 902-911 - [i24]David A. Moore, Stuart J. Russell:
Gaussian Process Random Fields. CoRR abs/1511.00054 (2015) - [i23]Hugh Chen, Yusuf Erol, Eric Shen, Stuart Russell:
Probabilistic Model-Based Approach for Heart Beat Detection. CoRR abs/1512.07931 (2015) - 2014
- [c101]Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, Pieter Abbeel:
Combined task and motion planning through an extensible planner-independent interface layer. ICRA 2014: 639-646 - [c100]Stuart Russell:
Unifying Logic and Probability: A New Dawn for AI? IPMU (1) 2014: 10-14 - [c99]Falk Lieder, Dillon Plunkett, Jessica B. Hamrick, Stuart J. Russell, Nicholas Hay, Thomas L. Griffiths:
Algorithm selection by rational metareasoning as a model of human strategy selection. NIPS 2014: 2870-2878 - [c98]David A. Moore, Stuart Russell:
Fast Gaussian Process Posteriors with Product Trees. UAI 2014: 613-622 - [c97]Siddharth Srivastava, Stuart Russell, Paul Ruan, Xiang Cheng:
First-Order Open-Universe POMDPs. UAI 2014: 742-751 - [i22]Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony:
Selecting Computations: Theory and Applications. CoRR abs/1408.2048 (2014) - 2013
- [c96]Lei Li, Bharath Ramsundar, Stuart Russell:
Dynamic Scaled Sampling for Deterministic Constraints. AISTATS 2013: 397-405 - [c95]Sharad Vikram, Lei Li, Stuart Russell:
Writing and sketching in the air, recognizing and controlling on the fly. CHI Extended Abstracts 2013: 1179-1184 - [c94]Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell:
The Extended Parameter Filter. ICML (3) 2013: 1103-1111 - [c93]Mark Rogers, Lei Li, Stuart Russell:
Multilinear Dynamical Systems for Tensor Time Series. NIPS 2013: 2634-2642 - [c92]Stuart Russell:
Rationality and Intelligence: A Brief Update. PT-AI 2013: 7-28 - [c91]David A. Moore, Stuart Russell:
Product Trees for Gaussian Process Covariance in Sublinear Time. UAI Application Workshops 2013: 58-66 - [i21]Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres:
Decayed MCMC Filtering. CoRR abs/1301.0584 (2013) - [i20]Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Michael I. Jordan, Stuart Russell:
Variational MCMC. CoRR abs/1301.2266 (2013) - [i19]Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell:
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. CoRR abs/1301.3853 (2013) - [i18]Nir Friedman, Kevin P. Murphy, Stuart Russell:
Learning the Structure of Dynamic Probabilistic Networks. CoRR abs/1301.7374 (2013) - [i17]Nir Friedman, Stuart Russell:
Image Segmentation in Video Sequences: A Probabilistic Approach. CoRR abs/1302.1539 (2013) - [i16]Keiji Kanazawa, Daphne Koller, Stuart Russell:
Stochastic Simulation Algorithms for Dynamic Probabilistic Networks. CoRR abs/1302.4965 (2013) - [i15]Stuart Russell:
Fine-Grained Decision-Theoretic Search Control. CoRR abs/1304.1133 (2013) - [i14]Sampath Srinivas, Stuart Russell, Alice M. Agogino:
Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information. CoRR abs/1304.1530 (2013) - [i13]Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell:
The Extended Parameter Filter. CoRR abs/1305.1704 (2013) - 2012
- [c90]Shaunak Chatterjee, Stuart Russell:
Uncertain Observation Times. SUM 2012: 392-405 - [c89]Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony:
Selecting Computations: Theory and Applications. UAI 2012: 346-355 - [i12]Shaunak Chatterjee, Stuart Russell:
A temporally abstracted Viterbi algorithm. CoRR abs/1202.3707 (2012) - [i11]Nimar S. Arora, Rodrigo de Salvo Braz, Erik B. Sudderth, Stuart Russell:
Gibbs Sampling in Open-Universe Stochastic Languages. CoRR abs/1203.3464 (2012) - [i10]Emma Brunskill, Stuart Russell:
RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains. CoRR abs/1203.3538 (2012) - [i9]Gregory Lawrence, Stuart Russell:
Improving Gradient Estimation by Incorporating Sensor Data. CoRR abs/1206.3272 (2012) - [i8]Brian Milch, Stuart Russell:
General-Purpose MCMC Inference over Relational Structures. CoRR abs/1206.6849 (2012) - [i7]Bhaskara Marthi, Stuart Russell, David Andre:
A compact, hierarchical Q-function decomposition. CoRR abs/1206.6851 (2012) - [i6]Eric P. Xing, Michael I. Jordan, Stuart Russell:
Graph partition strategies for generalized mean field inference. CoRR abs/1207.4156 (2012) - [i5]Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony:
Selecting Computations: Theory and Applications. CoRR abs/1207.5879 (2012) - [i4]Gregory Lawrence, Noah J. Cowan, Stuart Russell:
Efficient Gradient Estimation for Motor Control Learning. CoRR abs/1212.2475 (2012) - [i3]Eric P. Xing, Michael I. Jordan, Stuart Russell:
A Generalized Mean Field Algorithm for Variational Inference in Exponential Families. CoRR abs/1212.2512 (2012) - 2011
- [c88]