Zobrazeno 1 - 10
of 1 404
pro vyhledávání: '"Ivanov, Dmitry A."'
In real applications of Reinforcement Learning (RL), such as robotics, low latency and energy efficient inference is very desired. The use of sparsity and pruning for optimizing Neural Network inference, and particularly to improve energy and latency
Externí odkaz:
http://arxiv.org/abs/2405.07748
We consider linear search for an escaping target whose speed and initial position are unknown to the searcher. A searcher (an autonomous mobile agent) is initially placed at the origin of the real line and can move with maximum speed $1$ in either di
Externí odkaz:
http://arxiv.org/abs/2404.14300
Autor:
Iakovlev, Zakhar, Chulkov, Alexey, Golikov, Nikita, Lukianov, Vyacheslav, Zinoviev, Nikita, Ivanov, Dmitry, Aksenov, Vitaly
One common way to speed up the find operation within a set of text files involves a trigram index. This structure is merely a map from a trigram (sequence consisting of three characters) to a set of files which contain it. When searching for a patter
Externí odkaz:
http://arxiv.org/abs/2403.03751
Autor:
Ivanov, Dmitry, Ben-Porat, Omer
Personalization in machine learning (ML) tailors models' decisions to the individual characteristics of users. While this approach has seen success in areas like recommender systems, its expansion into high-stakes fields such as healthcare and autono
Externí odkaz:
http://arxiv.org/abs/2401.06514
Autor:
Bu, Caixia, Morrissey, Liam S., Bostick, Benjamin C., Burger, Matthew H., Bowen, Kyle P., Chillrud, Steven N., Domingue, Deborah L., Dukes, Catherine A., Ebel, Denton S., Harlow, George E., Hillenbrand, Pierre-Michel, Ivanov, Dmitry A., Killen, Rosemary M., Ross, James M., Schury, Daniel, Tucker, Orenthal J., Urbain, Xavier, Zhang, Ruitian, Savin, Daniel W.
We have measured the absolute doubly differential angular sputtering yield for 20 keV Kr+ impacting a polycrystalline Cu slab at an incidence angle of {\theta}i = 45{\deg} relative to the surface normal. Sputtered Cu atoms were captured using collect
Externí odkaz:
http://arxiv.org/abs/2312.12208
Autor:
Celiberto, Francesco Giovanni, Fucilla, Michael, Ivanov, Dmitry Yu., Mohammed, Mohammed M. A., Papa, Alessandro
We present the full next-to-leading order (NLO) result for the impact factor of a forward Higgs boson, obtained in the infinite-top-mass limit, both in the momentum representation and as superposition of the eigenfunctions of the leading-order (LO) B
Externí odkaz:
http://arxiv.org/abs/2309.07570
Publikováno v:
NeurIPS 2023
Contract design involves a principal who establishes contractual agreements about payments for outcomes that arise from the actions of an agent. In this paper, we initiate the study of deep learning for the automated design of optimal contracts. We i
Externí odkaz:
http://arxiv.org/abs/2307.02318
Publikováno v:
AAMAS '23, Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (May 2023) Pages 49-57
The majority of Multi-Agent Reinforcement Learning (MARL) literature equates the cooperation of self-interested agents in mixed environments to the problem of social welfare maximization, allowing agents to arbitrarily share rewards and private infor
Externí odkaz:
http://arxiv.org/abs/2306.08419
Autor:
Celiberto, Francesco Giovanni, Fucilla, Michael, Ivanov, Dmitry Yu., Mohammed, Mohammed M. A., Papa, Alessandro
It has been recently argued that the inclusive hadroproduction at the LHC of a Higgs boson in association with a jet can be sensitive to the high-energy dynamics. Moreover, the impact of the resummation at FCC energies is expected to be large also in
Externí odkaz:
http://arxiv.org/abs/2305.11760
In this work, we present a new benchmarking suite with new real-life inspired skewed workloads to test the performance of concurrent index data structures. We started this project to prepare workloads specifically for self-adjusting data structures,
Externí odkaz:
http://arxiv.org/abs/2305.10872