D. Vengerov

发表

A fuzzy reinforcement learning approach to power control in wireless transmitters

Nicholas Bambos, Hamid R. Berenji, David Vengerov, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

A convergent actor-critic-based FRL algorithm with application to power management of wireless transmitters

Hamid R. Berenji, David Vengerov, H. Berenji, 2003, IEEE Trans. Fuzzy Syst..

On convergence of fuzzy reinforcement learning

Hamid R. Berenji, David Vengerov, H. Berenji, 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

A Methodology for Developing Simple and Robust Power Models Using Performance Monitoring Events

D. Vengerov, Alexandra Fedorova, K. Pusukuri, 2009 .

Gated Experts for Classification of Financial Time Series

D. Vengerov, 1997 .

A gradient-based reinforcement learning approach to dynamic pricing in partially-observable environments

David Vengerov, D. Vengerov, 2008, Future Gener. Comput. Syst..

Adaptive Optimization of the JavaTM Real-Time System Garbage Collector

D. Vengerov, Qian Zhu, 2009 .

Adaptive Communication and Coordination in Multi-agent Systems

D. Vengerov, 2000 .

An Empirical Model of Factor Adjustment Dynamics

D. Vengerov, H. R. Berenji, H. Berenji, 2006 .

Cooperation and coordination between fuzzy reinforcement learning agents in continuous state partially observable Markov decision processes

H.R. Berenji, D. Vengerov, H. Berenji, 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

Context-sensitive planning for autonomous vehicles

David Vengerov, D. Vengerov, 1998 .

Machine learning multi-omics analysis reveals cancer driver dysregulation in pan-cancer cell lines compared to primary tumors

Holly C. Beale, Lauren M. Sanders, D. Haussler, 2022, Communications biology.

Dynamic adaptation of user migration policies in distributed virtual environments

David Vengerov, D. Vengerov, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A reinforcement learning framework for online data migration in hierarchical storage systems

David Vengerov, D. Vengerov, 2007, The Journal of Supercomputing.

Dynamic tuning of online data migration policies in hierarchical storage systems using reinforcement learning

David Vengerov, D. Vengerov, 2006 .

Placement of Virtual Containers on NUMA systems: A Practical and Comprehensive Model

Vivien Quéma, Jean-Pierre Lozi, Alexandra Fedorova, 2018, USENIX Annual Technical Conference.

Adaptive data-aware utility-based scheduling in resource-constrained systems

Nicholas Bambos, Declan Murphy, David Vengerov, 2010, J. Parallel Distributed Comput..

A reinforcement learning framework for utility-based scheduling in resource-constrained systems

David Vengerov, D. Vengerov, 2009, Future Gener. Comput. Syst..

Join Size Estimation Subject to Filter Conditions

David Vengerov, Mohamed Zaït, Sunil Chakkappen, 2015, Proc. VLDB Endow..

Using fuzzy reinforcement learning for power control in wireless transmitters

D. Vengerov, H. R. Berenji, H. Berenji, 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

A Reinforcement Learning Approach to Dynamic Resource Allocation ∗

David Vengerov, D. Vengerov, David Vengerov Sun, 2005 .

A Two-List Framework for Accurate Detection of Frequent Items in Data Streams

David Vengerov, D. Vengerov, 2018, MLDM.

Modeling, analysis and throughput optimization of a generational garbage collector

David Vengerov, D. Vengerov, 2009, ISMM '09.

Learning, Cooperation, and Coordination in Multi-Agent Systems

D. Vengerov, Hamid R. Berenji, H. Berenji, 2000 .

A reinforcement learning approach to dynamic resource allocation

D. Vengerov, 2007, Engineering applications of artificial intelligence.

A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results.

David Vengerov, Nikolai Iakovlev, D. Vengerov, 2005, Second International Conference on Autonomic Computing (ICAC'05).

Comprehensive multivariate extrapolation modeling of multiprocessor cache miss rates

David Vengerov, Ilya Gluhovsky, Brian O'Krafka, 2007, TOCS.

Constrained Multivariate Extrapolation Models With Application to Computer Cache Rates

David Vengerov, Ilya Gluhovsky, D. Vengerov, 2007, Technometrics.

A Methodology for Developing Simple and Robust Power Models Using Performance Monitoring Events

D. Vengerov, Alexandra Fedorova, K. Pusukuri, 2009 .

FACT: a framework for adaptive contention-aware thread migrations

Vana Kalogeraki, Kishore Kumar Pusukuri, Alexandra Fedorova, 2011, CF '11.