Georg Ostrovski

36 papers A* 11A 1Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	An Analysis of Quantile Temporal-Difference Learning. J. Mach. Learn. Res. Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney
2023	J	`jnl`	An Analysis of Quantile Temporal-Difference Learning. CoRR Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney
2023	A*	`conf`	Deep Reinforcement Learning with Plasticity Injection. NeurIPS Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
2023	J	`jnl`	Deep Reinforcement Learning with Plasticity Injection. CoRR Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
2023	A*	`conf`	Quantile Credit Assignment. ICML Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos
2022	J	`jnl`	An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet
2022	J	`jnl`	An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet
2022	A*	`conf`	The Phenomenon of Policy Churn. NeurIPS Tom Schaul, André Barreto, John Quan, Georg Ostrovski
2022	J	`jnl`	The Phenomenon of Policy Churn. CoRR Tom Schaul, André Barreto, John Quan, Georg Ostrovski
2022	A*	`conf`	When should agents explore? ICLR Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana L. Borsa, Tom Schaul
2021	J	`jnl`	On The Effect of Auxiliary Tasks on Representation Dynamics. CoRR Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney
2021	A	`conf`	On the Effect of Auxiliary Tasks on Representation Dynamics. AISTATS Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney
2021	J	`jnl`	Return-based Scaling: Yet Another Normalisation Trick for Deep RL. CoRR Tom Schaul, Georg Ostrovski, Iurii Kemaev, Diana Borsa
2021	A*	`conf`	Temporally-Extended ε-Greedy Exploration. ICLR Will Dabney, Georg Ostrovski, André Barreto
2021	A*	`conf`	The Difficulty of Passive Learning in Deep Reinforcement Learning. NeurIPS Georg Ostrovski, Pablo Samuel Castro, Will Dabney
2021	J	`jnl`	The Difficulty of Passive Learning in Deep Reinforcement Learning. CoRR Georg Ostrovski, Pablo Samuel Castro, Will Dabney
2021	J	`jnl`	When should agents explore? CoRR Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana Borsa, Tom Schaul
2020	J	`jnl`	Temporally-Extended ε-Greedy Exploration. CoRR Will Dabney, Georg Ostrovski, André Barreto
2019	J	`jnl`	Adapting Behaviour for Learning Progress. CoRR Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero
2019	—	`conf`	Recurrent Experience Replay in Distributed Reinforcement Learning. ICLR (Poster) Steven Kapturowski, Georg Ostrovski, John Quan, Rémi Munos, Will Dabney
2018	A*	`conf`	Autoregressive Quantile Networks for Generative Modeling. ICML Georg Ostrovski, Will Dabney, Rémi Munos
2018	J	`jnl`	Autoregressive Quantile Networks for Generative Modeling. CoRR Georg Ostrovski, Will Dabney, Rémi Munos
2018	A*	`conf`	Implicit Quantile Networks for Distributional Reinforcement Learning. ICML Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
2018	J	`jnl`	Implicit Quantile Networks for Distributional Reinforcement Learning. CoRR Will Dabney, Georg Ostrovski, David Silver, Rémi Munos
2018	A*	`conf`	Rainbow: Combining Improvements in Deep Reinforcement Learning. AAAI Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
2017	A*	`conf`	Count-Based Exploration with Neural Density Models. ICML Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
2017	J	`jnl`	Count-Based Exploration with Neural Density Models. CoRR Georg Ostrovski, Marc G. Bellemare, Aäron van den Oord, Rémi Munos
2017	J	`jnl`	Rainbow: Combining Improvements in Deep Reinforcement Learning. CoRR Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Daniel Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver
2017	J	`jnl`	Symmetric Decomposition of Asymmetric Games. CoRR Karl Tuyls, Julien Pérolat, Marc Lanctot, Georg Ostrovski, Rahul Savani, Joel Z. Leibo, Toby Ord, Thore Graepel, Shane Legg
2016	J	`jnl`	Hybrid computing using a neural network with dynamic external memory. Nat. Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John P. Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, Demis Hassabis
2016	A*	`conf`	Increasing the Action Gap: New Operators for Reinforcement Learning. AAAI Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
2016	—	`conf`	Unifying Count-Based Exploration and Intrinsic Motivation. NIPS Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
2016	J	`jnl`	Unifying Count-Based Exploration and Intrinsic Motivation. CoRR Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos
2015	J	`jnl`	Human-level control through deep reinforcement learning. Nat. Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
2015	J	`jnl`	Increasing the Action Gap: New Operators for Reinforcement Learning. CoRR Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos
2013	J	`jnl`	Payoff Performance of Fictitious Play. CoRR Georg Ostrovski, Sebastian van Strien

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.