A Multi-view Content-Based User Recommendation Scheme for Following Users in Twitter. - Milen Chechev; Petko Georgiev (SocInfo, 2012)

The Call of the Crowd: Event Participation in Location-Based Social Services. - Petko Georgiev; Anastasios Noulas; Cecilia Mascolo (ICWSM, 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 (ICWSM, 2014)

DSP.Ear: leveraging co-processor support for continuous audio sensing on smartphones. - Petko Georgiev; Nicholas D. Lane; Kiran K. Rachuri; Cecilia Mascolo (SenSys, 2014)

DeepEar: robust smartphone audio sensing in unconstrained acoustic environments using deep learning. - Nicholas D. Lane; Petko Georgiev; Lorena Qendro (UbiComp, 2015)

Energy Efficient and Fair Management of Sensing Applications on Heterogeneous Resource Mobile Devices. - Petko Georgiev (MobiSys PhDForum, 2015)

ZOE: A Cloud-less Dialog-enabled Continuous Sensing Wearable Exploiting Heterogeneous Computation. - Nicholas D. Lane; Petko Georgiev; Cecilia Mascolo; Ying Gao (MobiSys, 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 (IoT-App@SenSys, 2015)

Can Deep Learning Revolutionize Mobile Sensing? - Nicholas D. Lane; Petko Georgiev (HotMobile, 2015)

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Lei Jiao 002; Lorena Qendro; Fahim Kawsar (IPSN, 2016)

Demonstration Abstract: Accelerating Embedded Deep Learning Using DeepX. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (IPSN, 2016)

LEO: scheduling sensor inference algorithms across heterogeneous mobile processors and network resources. - Petko Georgiev; Nicholas D. Lane; Kiran K. Rachuri; Cecilia Mascolo (MobiCom, 2016)

Demo: Accelerated Deep Learning Inference for Embedded and Wearable Devices using DeepX. - Nicholas D. Lane; Sourav Bhattacharya; Petko Georgiev; Claudio Forlivesi; Fahim Kawsar (MobiSys (Companion Volume), 2016)

Accelerating Mobile Audio Sensing Algorithms through On-Chip GPU Offloading. - Petko Georgiev; Nicholas D. Lane; Cecilia Mascolo; David Chu (MobiSys, 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; et al. (CoRR, 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)

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)

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; et al. (Nat., 2019)

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; et al. (CoRR, 2020)

Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning. - Josh Abramson; Arun Ahuja; Arthur Brussee; Federico Carnevale; Mary Cassin; Felix Fischer 004; Petko Georgiev; Alex Goldin; Tim Harley; Felix Hill; Peter Conway Humphreys; Alden Hung; et al. (CoRR, 2021)

A data-driven approach for learning to control computers. - Peter Conway Humphreys; David Raposo; Tobias Pohlen; Gregory Thornton; Rachita Chhaparia; Alistair Muldal; Josh Abramson; Petko Georgiev; Adam Santoro; Timothy P. Lillicrap (ICML, 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 (NeurIPS, 2022)

A data-driven approach for learning to control computers. - Peter Conway Humphreys; David Raposo; Toby Pohlen; Gregory Thornton; Rachita Chhaparia; Alistair Muldal; Josh Abramson; Petko Georgiev; Alex Goldin; Adam Santoro; Timothy P. Lillicrap (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; et al. (CoRR, 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; et al. (CoRR, 2022)

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; et al. (CoRR, 2023)