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ORCIDBruno C. da Silva 0001
Person information
- affiliation: University of Massachusetts, Amherst, MA, USA
- affiliation (former): Federal University of Rio Grande do Sul (UFRGS), Institute of Informatics, Porto Alegre, Brazil
Other persons with the same name
- Bruno da Silva 0002
![[0000-0002-6467-9943]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-6467-9943")
(aka: Bruno Carreiro da Silva, Bruno C. da Silva 0002) — California Polytechnic State University, San Luis Obispo, CA, USA (and 1 more)
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Journal Articles
- 2021
[j6]Grasiela Marcon, Flávia de Ávila Pereira, Aline Zimerman, Bruno Castro da Silva, Lisia von Diemen, Ives Cavalcante Passos, Mariana Recamonde Mendoza:
Patterns of high-risk drinking among medical students: A web-based survey with machine learning. Comput. Biol. Medicine 136: 104747 (2021)- [j5]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Quantifying the impact of non-stationarity in reinforcement learning-based traffic signal control. PeerJ Comput. Sci. 7: e575 (2021) - 2020
- [j4]Michael Guilherme Jordan, Marcelo Brandalero, Guilherme Meneguzzi Malfatti, Geraldo F. Oliveira, Arthur Francisco Lorenzon, Bruno C. da Silva, Luigi Carro, Mateus B. Rutzig, Antonio Carlos Schneider Beck:
Data clustering for efficient approximate computing. Des. Autom. Embed. Syst. 24(1): 3-22 (2020) - [j3]Gabriel de Oliveira Ramos, Bruno C. da Silva, Roxana Radulescu, Ana L. C. Bazzan, Ann Nowé:
Toll-based reinforcement learning for efficient equilibria in route choice. Knowl. Eng. Rev. 35: e8 (2020) - 2018
- [j2]Rafael Garcia, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba:
A task-and-technique centered survey on visual analytics for deep learning model engineering. Comput. Graph. 77: 30-49 (2018) - 2010
- [j1]Ana L. C. Bazzan, Denise de Oliveira, Bruno Castro da Silva:
Learning in groups of traffic signals. Eng. Appl. Artif. Intell. 23(4): 560-568 (2010)
Conference and Workshop Papers
- 2024
- [c41]Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva:
From Past to Future: Rethinking Eligibility Traces. AAAI 2024: 12253-12260 - [c40]Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas:
Position: Benchmarking is Limited in Reinforcement Learning Research. ICML 2024 - 2023
- [c39]Lucas Nunes Alegre, Ana L. C. Bazzan, Diederik M. Roijers, Ann Nowé, Bruno C. da Silva:
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization. AAMAS 2023: 2003-2012 - [c38]Austin Hoag, James E. Kostas, Bruno Castro da Silva, Philip S. Thomas, Yuriy Brun:
Seldonian Toolkit: Building Software with Safe and Fair Machine Learning. ICSE Companion 2023: 107-111 - [c37]Lucas Nunes Alegre, Ana L. C. Bazzan, Ann Nowé, Bruno C. da Silva:
Multi-Step Generalized Policy Improvement by Leveraging Approximate Models. NeurIPS 2023 - [c36]Florian Felten, Lucas N. Alegre, Ann Nowé, Ana L. C. Bazzan, El-Ghazali Talbi, Grégoire Danoy, Bruno C. da Silva:
A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning. NeurIPS 2023 - [c35]Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno C. da Silva:
Behavior Alignment via Reward Function Optimization. NeurIPS 2023 - 2022
- [c34]Ørjan Strand, Didrik Spanne Reilstad, Zhenying Wu, Bruno Castro da Silva, Jim Torresen, Kai Olav Ellefsen:
RADAR: Reactive and Deliberative Adaptive Reasoning - Learning When to Think Fast and When to Think Slow. ICDL 2022: 184-189 - [c33]Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum:
Fairness Guarantees under Demographic Shift. ICLR 2022 - [c32]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer. ICML 2022: 394-413 - [c31]Nicholas Polosky, Bruno C. da Silva, Madalina Fiterau, Jithin Jagannath:
Constrained Offline Policy Optimization. ICML 2022: 17801-17810 - [c30]Isadora P. Possebon, Bruno Castro da Silva, Alberto E. Schaeffer-Filho:
Look-Ahead Reinforcement Learning for Load Balancing Network Traffic. ISCC 2022: 1-6 - [c29]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-stationary Environments. NeurIPS 2022 - 2021
- [c28]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection. AAMAS 2021: 97-105 - [c27]Chris Nota, Philip S. Thomas, Bruno C. da Silva:
Posterior Value Functions: Hindsight Baselines for Policy Gradient Methods. ICML 2021: 8238-8247 - [c26]Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. NeurIPS 2021: 27475-27490 - 2019
- [c25]Francisco M. Garcia, Bruno C. da Silva, Philip S. Thomas:
A Compression-Inspired Framework for Macro Discovery. AAMAS 2019: 1973-1975 - [c24]Aline Weber, Charles P. Martin, Jim Tørresen, Bruno C. da Silva:
Identifying Reusable Early-Life Options. ICDL-EPIROB 2019: 335-340 - [c23]Rafael Garcia, Alexandre Xavier Falcão, Alexandru C. Telea, Bruno Castro da Silva, Jim Tørresen, João Luiz Dihl Comba:
A Methodology for Neural Network Architectural Tuning Using Activation Occurrence Maps. IJCNN 2019: 1-10 - [c22]Aline Weber, Lucas Nunes Alegre, Jim Tørresen, Bruno C. da Silva:
Parameterized Melody Generation with Autoencoders and Temporally-Consistent Noise. NIME 2019: 174-179 - 2018
- [c21]Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan:
Towards Designing Optimal Reward Functions in Multi-Agent Reinforcement Learning Problems. IJCNN 2018: 1-8 - [c20]Thiago Bell Felix de Oliveira, Ana L. C. Bazzan, Bruno C. da Silva, Ricardo Grunitzki:
Comparing Multi-Armed Bandit Algorithms and Q-learning for Multiagent Action Selection: a Case Study in Route Choice. IJCNN 2018: 1-8 - [c19]Marcelo Brandalero, Guilherme Meneguzzi Malfatti, Geraldo Francisco Oliveira, Leonardo Almeida da Silveira, Larissa Rozales Gonçalves, Bruno Castro da Silva, Luigi Carro, Antonio Carlos Schneider Beck:
Efficient Local Memory Support for Approximate Computing. SBESC 2018: 122-129 - 2017
- [c18]Gabriel de Oliveira Ramos, Bruno Castro da Silva, Ana L. C. Bazzan:
Learning to Minimise Regret in Route Choice. AAMAS 2017: 846-855 - [c17]Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang:
Context-Based Concurrent Experience Sharing in Multiagent Systems. AAMAS 2017: 1544-1546 - [c16]Ricardo Grunitzki, Bruno Castro da Silva, Ana L. C. Bazzan:
A Flexible Approach for Designing Optimal Reward Functions. AAMAS 2017: 1559-1561 - [c15]Rafael Garcia, Bruno Castro da Silva, João Luiz Dihl Comba:
Task-based behavior generalization via manifold clustering. IROS 2017: 6047-6052 - 2016
- [c14]Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill:
Energetic Natural Gradient Descent. ICML 2016: 2887-2895 - [c13]Fernando Stefanello, Bruno Castro da Silva, Ana L. C. Bazzan:
Using Topological Statistics to Bias and Accelerate Route Choice: Preliminary Findings in Synthetic and Real-World Road Networks. ATT@IJCAI 2016 - 2014
- [c12]Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto:
Active Learning of Parameterized Skills. ICML 2014: 1737-1745 - [c11]Bruno Castro da Silva, Gianluca Baldassarre, George Dimitri Konidaris, Andrew G. Barto:
Learning parameterized motor skills on a humanoid robot. ICRA 2014: 5239-5244 - 2013
- [c10]Daniel D. Corkill, Chongjie Zhang, Bruno Castro da Silva, Yoonheui Kim, Daniel Garant, Victor R. Lesser, Xiaoqin Zhang:
Biasing the behavior of organizationally adept agents: (extended abstract). AAMAS 2013: 1309-1310 - 2012
- [c9]Bruno Castro da Silva, Andrew G. Barto:
TD-DeltaPi: A Model-Free Algorithm for Efficient Exploration. AAAI 2012: 886-892 - [c8]Bruno Castro da Silva, George Dimitri Konidaris, Andrew G. Barto:
Learning Parameterized Skills. ICML 2012 - 2007
- [c7]Ana L. C. Bazzan, Bruno Castro da Silva:
Distributed constraint propagation for diagnosis of faults in physical processes. AAMAS 2007: 119 - 2006
- [c6]Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel:
RL-CD: Dealing with Non-Stationarity in Reinforcement Learning. AAAI 2006: 1863-1864 - [c5]Bruno Castro da Silva, Eduardo W. Basso, Filipo Studzinski Perotto, Ana L. C. Bazzan, Paulo Martins Engel:
Improving reinforcement learning with context detection. AAMAS 2006: 810-812 - [c4]Bruno Castro da Silva, Robert Junges, Denise de Oliveira, Ana L. C. Bazzan:
ITSUMO: an Intelligent Transportation System for Urban Mobility. AAMAS 2006: 1471-1472 - [c3]Denise de Oliveira, Ana L. C. Bazzan, Bruno Castro da Silva, Eduardo W. Basso, Luís Nunes:
Reinforcement Learning based Control of Traffic Lights in Non-stationary Environments: A Case Study in a Microscopic Simulator. EUMAS 2006 - [c2]Bruno Castro da Silva, Eduardo W. Basso, Ana L. C. Bazzan, Paulo Martins Engel:
Dealing with non-stationary environments using context detection. ICML 2006: 217-224 - 2004
- [c1]Bruno Castro da Silva, Ana L. C. Bazzan, Gustavo Kuhn Andriotti, Filipe Lopes, Denise de Oliveira:
ITSUMO: An Intelligent Transportation System for Urban Mobility. IICS 2004: 224-235
Informal and Other Publications
- 2024
- [i19]Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, Ameet Deshpande, Bruno Castro da Silva:
RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs. CoRR abs/2404.08555 (2024) - [i18]Scott M. Jordan, Adam White, Bruno Castro da Silva, Martha White, Philip S. Thomas:
Position: Benchmarking is Limited in Reinforcement Learning Research. CoRR abs/2406.16241 (2024) - 2023
- [i17]Lucas Nunes Alegre, Ana L. C. Bazzan, Diederik M. Roijers, Ann Nowé, Bruno C. da Silva:
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization. CoRR abs/2301.07784 (2023) - [i16]Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas:
Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR abs/2301.10330 (2023) - [i15]James E. Kostas, Scott M. Jordan, Yash Chandak, Georgios Theocharous, Dhawal Gupta, Martha White, Bruno Castro da Silva, Philip S. Thomas:
Coagent Networks: Generalized and Scaled. CoRR abs/2305.09838 (2023) - [i14]Dhawal Gupta, Yash Chandak, Scott M. Jordan, Philip S. Thomas, Bruno Castro da Silva:
Behavior Alignment via Reward Function Optimization. CoRR abs/2310.19007 (2023) - [i13]Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas, Bruno Castro da Silva:
From Past to Future: Rethinking Eligibility Traces. CoRR abs/2312.12972 (2023) - 2022
- [i12]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer. CoRR abs/2206.11326 (2022) - [i11]Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas, Bruno Castro da Silva:
Enforcing Delayed-Impact Fairness Guarantees. CoRR abs/2208.11744 (2022) - [i10]Rushiv Arora, Bruno Castro da Silva, Eliot Moss:
Model-Based Reinforcement Learning with SINDy. CoRR abs/2208.14501 (2022) - 2021
- [i9]Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas:
Universal Off-Policy Evaluation. CoRR abs/2104.12820 (2021) - [i8]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection. CoRR abs/2105.09452 (2021) - 2020
- [i7]Manuel Del Verme, Bruno Castro da Silva, Gianluca Baldassarre:
Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints. CoRR abs/2001.01620 (2020) - [i6]Lucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva:
Quantifying the Impact of Non-Stationarity in Reinforcement Learning-Based Traffic Signal Control. CoRR abs/2004.04778 (2020) - [i5]Vieri Giuliano Santucci, Davide Montella, Bruno Castro da Silva, Gianluca Baldassarre:
Autonomous learning of multiple, context-dependent tasks. CoRR abs/2011.13847 (2020) - 2019
- [i4]Vieri Giuliano Santucci, Emilio Cartoni, Bruno Castro da Silva, Gianluca Baldassarre:
Autonomous Open-Ended Learning of Interdependent Tasks. CoRR abs/1905.02690 (2019) - 2017
- [i3]Daniel Garant, Bruno Castro da Silva, Victor R. Lesser, Chongjie Zhang:
Context-Based Concurrent Experience Sharing in Multiagent Systems. CoRR abs/1703.01931 (2017) - [i2]Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill:
On Ensuring that Intelligent Machines Are Well-Behaved. CoRR abs/1708.05448 (2017) - [i1]Francisco M. Garcia, Bruno C. da Silva:
Identifying Reusable Macros for Efficient Exploration via Policy Compression. CoRR abs/1711.09048 (2017)
Coauthor Index
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