Machine Learning Methods for Attack Detection in the Smart Grid
- M. Ozay, I. Esnaola, F. Yarman-Vural, S. Kulkarni, H. Poor
- Computer Science, EngineeringIEEE Transactions on Neural Networks and Learning…
- 22 March 2015
Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.
Divergence Estimation for Multidimensional Densities Via $k$-Nearest-Neighbor Distances
- Qing Wang, S. Kulkarni, S. Verdú
- Computer ScienceIEEE Transactions on Information Theory
- 1 May 2009
It is shown that the speed of convergence of the k-NN method can be further improved by an adaptive choice of k.i.d., and the new universal estimator of divergence is proved to be asymptotically unbiased and mean-square consistent.
A deterministic approach to throughput scaling in wireless networks
- S. Kulkarni, P. Viswanath
- Computer ScienceIEEE Transactions on Information Theory
- 12 September 2002
This work provides a very elementary deterministic approach that gives achievability results in terms of three key properties of the node locations of n identical nodes placed in a fixed area to address the problem of how throughput in a wireless network scales as the number of users grows.
The Problem of Induction
- G. Harman, S. Kulkarni
- Philosophy
- 1 May 2006
The problem of induction is sometimes motivated via a comparison between rules of induction and rules of deduction. Valid deductive rules are necessarily truth preserving, while inductive rules are…
Probabilistic Coherence and Proper Scoring Rules
- J. Predd, R. Seiringer, E. Lieb, D. Osherson, H. Poor, S. Kulkarni
- MathematicsIEEE Transactions on Information Theory
- 16 October 2007
This paper provides self-contained proof of a theorem relating probabilistic coherence of forecasts to their non-domination by rival forecasts with respect to any proper scoring rule. The theorem…
Rapid estimation of camera motion from compressed video with application to video annotation
- Yap-Peng Tan, D. D. Saur, S. Kulkarni, P. Ramadge
- Computer ScienceIEEE Trans. Circuits Syst. Video Technol.
- 1 February 2000
It is shown that in certain structured settings, it is possible to obtain reliable estimates of camera motion by directly processing data easily obtained from the MPEG format.
Divergence estimation of continuous distributions based on data-dependent partitions
- Qing Wang, S. Kulkarni, S. Verdú
- Mathematics, Computer ScienceIEEE Transactions on Information Theory
- 1 September 2005
A universal estimator of the divergence D(P/spl par/Q) for two arbitrary continuous distributions P and Q satisfying certain regularity conditions that achieves the best convergence performance in most of the tested cases.
Upper bounds to transport capacity of wireless networks
- A. Jovičić, P. Viswanath, S. Kulkarni
- Computer ScienceIEEE Transactions on Information Theory
- 1 November 2004
The optimality, in the sense of scaling of transport capacity with the number of nodes, of a multihop communication strategy for a class of network topologies is concluded.
A Nearest-Neighbor Approach to Estimating Divergence between Continuous Random Vectors
- Qing Wang, S. Kulkarni, S. Verdú
- Computer ScienceIEEE International Symposium on Information…
- 9 July 2006
A method for divergence estimation between multidimensional distributions based on nearest neighbor distances is proposed. Given i.i.d. samples, both the bias and the variance of this estimator are…
Distributed learning in wireless sensor networks
- J. Predd, S. Kulkarni, H. Poor
- Computer ScienceIEEE Signal Processing Magazine
- 25 March 2005
The challenges that wireless sensor networks pose for distributed learning are discussed, and research aimed at addressing these challenges is surveyed.
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