Data Mining Techniques for RoboCup Soccer Agents. - Lev Stankevich; Sergey Serebryakov; Anton Ivanov (AIS-ADM, 2005)

P2P Agent Platform: Implementation and Testing. - Vladimir Gorodetsky; Oleg Karsaev; Vladimir Samoilov; Sergey Serebryakov (AP2PC, 2007)

Automated P2P Learning in Agent-Based Classification Networks. - Vladimir Gorodetsky; Oleg Karsaev; Vladimir Samoilov; Sergey Serebryakov (Web Intelligence/IAT Workshops, 2007)

P2P Open Agent Networks for Decision Making. - Vladimir Gorodetsky; Oleg Karsaev; Vladimir Samoilov; Sergey Serebryakov (SYNASC, 2007)

Interaction of Agents and Data Mining in Ubiquitous Environment. - Vladimir Gorodetsky; Oleg Karsaev; Vladimir Samoilov; Sergey Serebryakov (Web Intelligence/IAT Workshops, 2008)

Agent-based distributed decision-making in dynamic operational environments. - Vladimir Gorodetsky; Oleg Karsaev; Vladimir Samoilov; Sergey Serebryakov (Intell. Decis. Technol., 2009)

Ontology - Based Context - Dependent Personalization Technology. - Vladimir Gorodetsky; Vladimir Samoilov; Sergey Serebryakov (Web Intelligence/IAT Workshops, 2010)

Context-driven data and information fusion. - Vladimir Gorodetsky; Vladimir Samoylov; Sergey Serebryakov (FUSION, 2012)

Knowledge-Based Behavior Specification. - Vladimir Gorodetsky; Vladimir Samoylov; D. Trotsky; Sergey Serebryakov (Web Intelligence/IAT Workshops, 2012)

Semi-Automatic Generation of Linear Event Extraction Patterns for Free Texts. - Daria Dzendzik; Sergey Serebryakov (SYRCoDIS, 2013)

Benchmarking Deep Learning for Time Series: Challenges and Directions. - Xinyuan Huang; Geoffrey C. Fox; Sergey Serebryakov; Ankur Mohan; Pawel M. Morkisz; Debojyoti Dutta (IEEE BigData, 2019)

Future Computing Systems (FCS) to Support "Understanding" Capability. - Raymond G. Beausoleil; Thomas Van Vaerenbergh; Kirk Bresniker; Catherine Graves; Kimberly Keeton; Suhas Kumar; Can Li; Dejan S. Milojicic; Sergey Serebryakov; John Paul Strachan (ICRC, 2019)

Deep Learning Cookbook: Recipes for your AI Infrastructure and Applications. - Sergey Serebryakov; Dejan S. Milojicic; Natalia Vassilieva; Stephen Fleischman; Robert D. Clark (ICRC, 2019)

Artificial Intelligence and Critical Systems: From Hype to Reality. - Phil Laplante; Dejan S. Milojicic; Sergey Serebryakov; Daniel Bennett (Computer, 2020)

Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. - Sitao Huang; Aayush Ankit; Plínio Silveira; Rodrigo Antunes; Sai Rahul Chalamalasetti; Izzat El Hajj; Dong Eun Kim; Glaucimar Aguiar; Pedro Bruel; Sergey Serebryakov; Cong Xu; Can Li; et al. (ASP-DAC, 2021)

Resource Sharing and Security Implications on Machine Learning Inference Accelerators. - Plínio Silveira; César Augusto Fonticielha De Rose; Avelino Francisco Zorzo; Miguel Gomes Xavier; Dejan S. Milojicic; Sai Rahul Chalamalasetti; Sergey Serebryakov (COMPSAC, 2021)

Survival of the Fittest Amidst the Cambrian Explosion of Processor Architectures for Artificial Intelligence : Invited Paper. - Sreenivas R. Sukumar 001; Jacob Balma; Cong Xu; Sergey Serebryakov (PEHC@SC, 2021)

Tree-based machine learning performed in-memory with memristive analog CAM. - Giacomo Pedretti; Catherine E. Graves; Can Li; Sergey Serebryakov; Xia Sheng; Martin Foltin; Ruibin Mao; John Paul Strachan (CoRR, 2021)

A general tree-based machine learning accelerator with memristive analog CAM. - Giacomo Pedretti; Sergey Serebryakov; John Paul Strachan; Catherine E. Graves (ISCAS, 2022)

Self-learning Data Foundation for Scientific AI. - Annmary Justine; Sergey Serebryakov; Cong Xu; Aalap Tripathy; Suparna Bhattacharya; Paolo Faraboschi; Martin Foltin (SMC, 2022)

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs. - Giacomo Pedretti; John Moon; Pedro Bruel; Sergey Serebryakov; Ron M. Roth; Luca Buonanno; Tobias Ziegler 006; Cong Xu; Martin Foltin; Paolo Faraboschi; Jim Ignowski; Catherine E. Graves (CoRR, 2023)

RACE-IT: A Reconfigurable Analog CAM-Crossbar Engine for In-Memory Transformer Acceleration. - Lei Zhao; Luca Buonanno; Ron M. Roth; Sergey Serebryakov; Archit Gajjar; John Moon; Jim Ignowski; Giacomo Pedretti (CoRR, 2023)

CAMSHAP: Accelerating Machine Learning Model Explainability with Analog CAM. - John Moon; Giacomo Pedretti; Pedro Bruel; Sergey Serebryakov; Omar Eldash; Luca Buonanno; Catherine E. Graves; Paolo Faraboschi; Jim Ignowski (ICCAD, 2024)

AIOps and Sustainability: Transforming Data Centers for a Greener Future. - Subrahmanya Vinayak Joshi; Sergey Serebryakov; Deepak Nanjundaiah; Tejas Hegde (SC Workshops, 2024)

Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization. - Revathy Venkataramanan; Aalap Tripathy; Tarun Kumar; Sergey Serebryakov; Annmary Justine; Arpit Shah; Suparna Bhattacharya; Martin Foltin; Paolo Faraboschi; Kaushik Roy 009; Amit P. Sheth (Frontiers Big Data, 2024)

Common Metadata Framework: Integrated Framework for Trustworthy Artificial Intelligence Pipelines. - Ann Mary Justine Koomthanam; Aalap Tripathy; Sergey Serebryakov; Gyanaranjan Nayak; Martin Foltin; Suparna Bhattacharya (IEEE Internet Comput., 2024)