David Vengerov - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 27 from 27

2023

Dynamic Embedding-based Retrieval for Personalized Item Recommendations at InstacartChuanwei Ruan, Allan Stewart, Han Li, Ryan Ye, David Vengerov, Haixun Wang. WWW 2023: 983-987 [doi]

2019

A Machine Learning Approach to Recommending Files in a Collaborative Work EnvironmentDavid Vengerov, Sesh Jalagam. sigops, 53(1):46-51, 2019. [doi]

2018

Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive ModelJustin R. Funston, Maxime Lorrillere, Alexandra Fedorova, Baptiste Lepers, David Vengerov, Jean-Pierre Lozi, Vivien Quéma. usenix 2018: 281-294 [doi]

A Two-List Framework for Accurate Detection of Frequent Items in Data StreamsDavid Vengerov. mldm 2018: 228-243 [doi]

2017

Dynamic adaptation of user migration policies in distributed virtual environmentsDavid Vengerov. ijcnn 2017: 4028-4035 [doi]

2015

The judgment of forseti: economic utility for dynamic heap sizing of multiple runtimesCallum Cameron, Jeremy Singer, David Vengerov. iwmm 2015: 143-156 [doi]

Join Size Estimation Subject to Filter ConditionsDavid Vengerov, Andre Cavalheiro Menck, Mohamed Zaït, Sunil Chakkappen. pvldb, 8(12):1530-1541, 2015. [doi]

2011

FACT: a framework for adaptive contention-aware thread migrationsKishore Kumar Pusukuri, David Vengerov, Alexandra Fedorova, Vana Kalogeraki. cf 2011: 35 [doi]

2010

Adaptive data-aware utility-based scheduling in resource-constrained systemsDavid Vengerov, Lykomidis Mastroleon, Declan Murphy, Nicholas Bambos. jpdc, 70(9):871-879, 2010. [doi]

2009

Modeling, analysis and throughput optimization of a generational garbage collectorDavid Vengerov. iwmm 2009: 1-9 [doi]

A reinforcement learning framework for utility-based scheduling in resource-constrained systemsDavid Vengerov. fgcs, 25(7):728-736, 2009. [doi]

2008

A reinforcement learning framework for online data migration in hierarchical storage systemsDavid Vengerov. tjs, 43(1):1-19, 2008. [doi]

A gradient-based reinforcement learning approach to dynamic pricing in partially-observable environmentsDavid Vengerov. fgcs, 24(7):687-693, 2008. [doi]

2007

Comprehensive multivariate extrapolation modeling of multiprocessor cache miss ratesIlya Gluhovsky, David Vengerov, Brian O Krafka. tocs, 25(1):2, 2007. [doi]

Constrained Multivariate Extrapolation Models With Application to Computer Cache RatesIlya Gluhovsky, David Vengerov. technometrics, 49(2):129-137, 2007. [doi]

A reinforcement learning approach to dynamic resource allocationDavid Vengerov. eaai, 20(3):383-390, 2007. [doi]

2005

Adaptive Utility-Based Scheduling in Resource-Constrained SystemsDavid Vengerov. ausai 2005: 477-488 [doi]

A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results.David Vengerov, Nikolai Iakovlev. icac 2005: 339-340 [doi]

A fuzzy reinforcement learning approach to power control in wireless transmittersDavid Vengerov, Nicholas Bambos, Hamid R. Berenji. tsmc, 35(4):768-778, 2005. [doi]

2004

Using gated experts in fault diagnosis and prognosisHamid R. Berenji, Yan Wang, David Vengerov, Reza Langari, Mo Jamshidi. fuzzIEEE 2004: 463-467 [doi]

2003

A convergent actor-critic-based FRL algorithm with application to power management of wireless transmittersHamid R. Berenji, David Vengerov. tfs, 11(4):478-485, 2003. [doi]

Co-evolutionary perception-based reinforcement learning for sensor allocation in autonomous vehiclesHamid R. Berenji, David Vengerov, Jayesh Ametha. fuzzIEEE 2003: 125-130 [doi]

Inductive learning for fault diagnosisHamid R. Berenji, Jayesh Ametha, David Vengerov. fuzzIEEE 2003: 726-731 [doi]

2002

Adaptive coordination among fuzzy reinforcement learning agents performing distributed dynamic load balancingDavid Vengerov, Hamid R. Berenji, Alex Vengerov. fuzzIEEE 2002: 179-184 [doi]

Using fuzzy reinforcement learning for power control in wireless transmittersDavid Vengerov, Hamid R. Berenji. fuzzIEEE 2002: 797-802 [doi]

2001

On Convergence of Fuzzy Reinforcement LearningHamid R. Berenji, David Vengerov. fuzzIEEE 2001: 618-621

2000

Advantages of cooperation between reinforcement learning agents in difficult stochastic problemsHamid R. Berenji, David Vengerov. fuzzIEEE 2000: 871-876 [doi]

Sign in or sign up to see more results.

runs on WebDSL