Petko Georgiev

According to our database, Petko Georgiev authored at least 26 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning.

Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals

CoRR, 2023

2022

Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback.

Josh Abramson, Arun Ahuja, Federico Carnevale, Petko Georgiev, Alex Goldin, Alden Hung, Jessica Landon, Jirka Lhotka, Timothy P. Lillicrap, Alistair Muldal, George Powell, Adam Santoro, Guy Scully, Sanjana Srivastava, Tamara von Glehn, Greg Wayne, Nathaniel Wong, Chen Yan, Rui Zhu

CoRR, 2022

Evaluating Multimodal Interactive Agents.

Josh Abramson, Arun Ahuja, Federico Carnevale, Petko Georgiev, Alex Goldin, Alden Hung, Jessica Landon, Timothy P. Lillicrap, Alistair Muldal, Blake A. Richards, Adam Santoro, Tamara von Glehn, Greg Wayne, Nathaniel Wong, Chen Yan

CoRR, 2022

A data-driven approach for learning to control computers.

Peter C. Humphreys, David Raposo, Toby Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal, Josh Abramson, Petko Georgiev, Alex Goldin, Adam Santoro, Timothy P. Lillicrap

CoRR, 2022

Intra-agent speech permits zero-shot task acquisition.

Chen Yan, Federico Carnevale, Petko Georgiev, Adam Santoro, Aurelia Guy, Alistair Muldal, Chia-Chun Hung, Josh Abramson, Timothy P. Lillicrap, Gregory Wayne

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A data-driven approach for learning to control computers.

Peter C. Humphreys, David Raposo, Tobias Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal, Josh Abramson, Petko Georgiev, Adam Santoro, Timothy P. Lillicrap

Proceedings of the International Conference on Machine Learning, 2022

2021

Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning.

Josh Abramson, Arun Ahuja, Arthur Brussee, Federico Carnevale, Mary Cassin, Felix Fischer, Petko Georgiev, Alex Goldin, Tim Harley, Felix Hill, Peter C. Humphreys, Alden Hung, Jessica Landon, Timothy P. Lillicrap, Hamza Merzic, Alistair Muldal, Adam Santoro, Guy Scully, Tamara von Glehn, Greg Wayne, Nathaniel Wong, Chen Yan, Rui Zhu

CoRR, 2021

2020

Imitating Interactive Intelligence.

Josh Abramson, Arun Ahuja, Arthur Brussee, Federico Carnevale, Mary Cassin, Stephen Clark, Andrew Dudzik, Petko Georgiev, Aurelia Guy, Tim Harley, Felix Hill, Alden Hung, Zachary Kenton, Jessica Landon, Timothy P. Lillicrap, Kory W. Mathewson, Alistair Muldal, Adam Santoro, Nikolay Savinov, Vikrant Varma, Greg Wayne, Nathaniel Wong, Chen Yan, Rui Zhu

CoRR, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

2017

Squeezing Deep Learning into Mobile and Embedded Devices.

Nicholas D. Lane, Sourav Bhattacharya, Akhil Mathur, Petko Georgiev, Claudio Forlivesi, Fahim Kawsar

IEEE Pervasive Comput., 2017

Low-resource Multi-task Audio Sensing for Mobile and Embedded Devices via Shared Deep Neural Network Representations.

Petko Georgiev, Sourav Bhattacharya, Nicholas D. Lane, Cecilia Mascolo

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017

StarCraft II: A New Challenge for Reinforcement Learning.

Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John P. Agapiou, Julian Schrittwieser, John Quan, Stephen Gaffney, Stig Petersen, Karen Simonyan, Tom Schaul, Hado van Hasselt, David Silver, Timothy P. Lillicrap, Kevin Calderone, Paul Keet, Anthony Brunasso, David Lawrence, Anders Ekermo, Jacob Repp, Rodney Tsing

CoRR, 2017

Accelerating Mobile Audio Sensing Algorithms through On-Chip GPU Offloading.

Petko Georgiev, Nicholas D. Lane, Cecilia Mascolo, David Chu

Proceedings of the 15th Annual International Conference on Mobile Systems, 2017

2016

Demo: Accelerated Deep Learning Inference for Embedded and Wearable Devices using DeepX.

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Fahim Kawsar

Proceedings of the 14th Annual International Conference on Mobile Systems, 2016

LEO: scheduling sensor inference algorithms across heterogeneous mobile processors and network resources.

Petko Georgiev, Nicholas D. Lane, Kiran K. Rachuri, Cecilia Mascolo

Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, 2016

Demonstration Abstract: Accelerating Embedded Deep Learning Using DeepX.

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Fahim Kawsar

Proceedings of the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2016

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices.

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, Fahim Kawsar

Proceedings of the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2016

2015

Can Deep Learning Revolutionize Mobile Sensing?

Nicholas D. Lane, Petko Georgiev

Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications, 2015

An Early Resource Characterization of Deep Learning on Wearables, Smartphones and Internet-of-Things Devices.

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Fahim Kawsar

Proceedings of the 2015 International Workshop on Internet of Things towards Applications, 2015

ZOE: A Cloud-less Dialog-enabled Continuous Sensing Wearable Exploiting Heterogeneous Computation.

Nicholas D. Lane, Petko Georgiev, Cecilia Mascolo, Ying Gao

Proceedings of the 13th Annual International Conference on Mobile Systems, 2015

Energy Efficient and Fair Management of Sensing Applications on Heterogeneous Resource Mobile Devices.

Petko Georgiev

Proceedings of the 2015 on MobiSys PhD Forum, Florence, Italy, 2015

DeepEar: robust smartphone audio sensing in unconstrained acoustic environments using deep learning.

Nicholas D. Lane, Petko Georgiev, Lorena Qendro

Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2015

2014

DSP.Ear: leveraging co-processor support for continuous audio sensing on smartphones.

Petko Georgiev, Nicholas D. Lane, Kiran K. Rachuri, Cecilia Mascolo

Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems, 2014

Where Businesses Thrive: Predicting the Impact of the Olympic Games on Local Retailers through Location-based Services Data.

Petko Georgiev, Anastasios Noulas, Cecilia Mascolo

Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

The Call of the Crowd: Event Participation in Location-Based Social Services.

Petko Georgiev, Anastasios Noulas, Cecilia Mascolo

Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

2012

A Multi-view Content-Based User Recommendation Scheme for Following Users in Twitter.

Milen Chechev, Petko Georgiev

Proceedings of the Social Informatics, 2012