Výsledky vyhledávání - "David Tolpin"

Publikováno v: Proceedings of the AAAI Conference on Artificial Intelligence. 26:570-576

UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs fro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::00870a8cedc7a51094b48ca6dd4aef68
https://doi.org/10.1609/aaai.v26i1.8126

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MCTS Based on Simple Rerget

Autor: David Tolpin, Solomon Shimony

Publikováno v: Proceedings of the International Symposium on Combinatorial Search. 3:193-199

UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS),is based on UCB, a policy for the Multi-armed Bandit problem (MAB) thatminimizes the cumulative regret. However, search differs from MAB inthat in MCTS it is usually only the final

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b69f5387cbe9f8605ef40e8cc04f263a
https://doi.org/10.1609/socs.v3i1.18221

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ICBS: The Improved Conflict-Based Search Algorithm for Multi-Agent Pathfinding

Autor: Eli Boyarski, Ariel Felner, Roni Stern, Guni Sharon, Oded Betzalel, David Tolpin, Eyal Shimony

Publikováno v: Proceedings of the International Symposium on Combinatorial Search. 6:223-225

Conflict-Based Search (CBS) and its generalization, Meta-Agent CBS are amongst the strongest newly introduced algorithms for Multi-Agent Path Finding. This paper introduces ICBS, an improved version of CBS. ICBS incorporates three orthogonal improvem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::998f9d62c1b46405128a1af99bdb9f73
https://doi.org/10.1609/socs.v6i1.18343

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Monitoring Time Series with Missing Values: A Deep Probabilistic Approach

Autor: Oshri Barazani, David Tolpin

Publikováno v: Cyber Security, Cryptology, and Machine Learning ISBN: 9783031076886

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e64f475212f56085819868be666155a7
https://doi.org/10.1007/978-3-031-07689-3_2

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Warped Input Gaussian Processes for Time Series Forecasting

Autor: David Tolpin, Igor Vinokur

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030780852
CSCML

Time series forecasting plays a vital role in system monitoring and novelty detection. However, commonly used forecasting methods are not suited for handling non-stationarity, while existing methods for forecasting in non-stationary time series are o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9e76d94ccac869bb606c5a22b1cfb7b1
https://doi.org/10.1007/978-3-030-78086-9_16

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Rational deployment of multiple heuristics in optimal state-space search

Autor: Erez Karpas, Oded Betzalel, Ariel Felner, Solomon Eyal Shimony, David Tolpin

Publikováno v: Artificial Intelligence. 256:181-210

The obvious way to use several admissible heuristics in searching for an optimal solution is to take their maximum. In this paper, we aim to reduce the time spent on computing heuristics within the context of A ⁎ and I D A ⁎ . We discuss Lazy A �

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7ca81f8b660e74c850bf9b70c45ebaf9
https://doi.org/10.1016/j.artint.2017.11.001

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Deployable probabilistic programming

Autor: David Tolpin

Publikováno v: Onward!

We propose design guidelines for a probabilistic programming facility suitable for deployment as a part of a production software system. As a reference implementation, we introduce Infergo, a probabilistic programming facility for Go, a modern progra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c24b6feb42434d10f05e39211467e38
http://arxiv.org/abs/1906.11199

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Population Anomaly Detection through Deep Gaussianization

Autor: David Tolpin

Publikováno v: SAC

We introduce an algorithmic method for population anomaly detection based on gaussianization through an adversarial autoencoder. This method is applicable to detection of `soft' anomalies in arbitrarily distributed highly-dimensional data. A soft, or

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fa010fc83248a6dae665754f079b9fb
http://arxiv.org/abs/1805.02123

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A Planning Approach to Monitoring Computer Programs’ Behavior

Autor: Ronen I. Brafman, David Tolpin, Alexandre Cukier, Yotam Perkal

Publikováno v: Lecture Notes in Computer Science ISBN: 9783319941462
CSCML

We describe a novel approach to monitoring high level behaviors using concepts from AI planning. Our goal is to understand what a program is doing based on its system call trace. This ability is particularly important for detecting malware. We approa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c8f757c875ef864df19623706d7eb101
https://doi.org/10.1007/978-3-319-94147-9_19

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Process Monitoring on Sequences of System Call Count Vectors

Autor: Benjamin Myara, David Tolpin, Michael Dymshits

Publikováno v: ICCST

We introduce a methodology for efficient monitoring of processes running on hosts in a corporate network. The methodology is based on collecting streams of system calls produced by all or selected processes on the hosts, and sending them over the net

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f9da4c5c8ca485c69e94022027a359b
http://arxiv.org/abs/1707.03821

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