Tsitsiklis, John N.Overview
Publication Timeline
Most widely held works by
John N Tsitsiklis
Parallel and distributed computation : numerical methods
by Dimitri P Bertsekas
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Book
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21 editions published between 1989 and 1997 in English and held by 535 WorldCat member libraries worldwide Mathematics of Computing  Parallelism
Introduction to linear optimization
by Dimitris Bertsimas
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Book
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9 editions published in 1997 in English and Spanish and held by 296 WorldCat member libraries worldwide
Neurodynamic programming
by Dimitri P Bertsekas
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Book
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10 editions published between 1996 and 1999 in English and held by 260 WorldCat member libraries worldwide
Introduction to probability
by Dimitri P Bertsekas
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Book
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17 editions published between 2002 and 2008 in English and held by 252 WorldCat member libraries worldwide
An optimal multigrid algorithm for continuous state discrete time stochastic control
by CheeSeng Chow
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Book
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6 editions published between 1988 and 1989 in English and held by 9 WorldCat member libraries worldwide
On the average communication complexity of asynchronous distributed algorithms
by John N Tsitsiklis
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Book
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4 editions published between 1990 and 1996 in English and held by 6 WorldCat member libraries worldwide Abstract: "We study the communication complexity of asychronous distributed algorithms, such as the distributed BellmanFord algorithm for the shortest path problem. Such algorithms can generate excessively many messages in the worst case. Nevertheless, we show that under certain probabilistic assumptions, the expected number of messages generated per time unit is bounded by a polynomial function of the number of processors. We conclude that (under our model) any asynchronous algorithm with good time complexity will also have good communication complexity, on the average."
On a lower bound for the redundancy of reliable networks with noisy gates
by Nicholas Pippenger
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Book
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4 editions published in 1990 in English and held by 6 WorldCat member libraries worldwide
Data fusion with minimal communication
by Z.Q Luo
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Book
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4 editions published between 1991 and 1993 in English and held by 6 WorldCat member libraries worldwide
The throughput of a precedencebased queuing discipline
by John N Tsitsiklis
(
Book
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1 edition published in 1984 in English and held by 6 WorldCat member libraries worldwide
On the settling time of the congested G/G/1 queue
by G. D Stamoulis
(
Book
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3 editions published in 1989 in English and held by 5 WorldCat member libraries worldwide
On the predictability of coupled automata : an allegory about chaos
by Samuel R Buss
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Book
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3 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide
The worst bulk arrival process to a queue
by Daniel C Lee
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Book
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3 editions published in 1992 in English and held by 5 WorldCat member libraries worldwide
An analysis of stochastic shortest path problems
by Dimitri P Bertsekas
(
Book
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4 editions published in 1988 in English and held by 5 WorldCat member libraries worldwide
A comparison of Jacobi and GaussSeidel parallel iterations
by John N Tsitsiklis
(
Book
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3 editions published in 1988 in English and held by 5 WorldCat member libraries worldwide
Active learning using arbitrary binary valued queries
by Sanjeev R Kulkarni
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Book
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3 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide The original and most widely studied PAC model for learning assumes a passive learner in the sense that the learner plays no role in obtaining information about the unknown concept. That is, the samples are simply drawn independently from some probability distribution. Some work has been done on studying more powerful oracles and how they affect learnability. To find bounds on the improvement that can be expected from using oracles, we consider active learning in the sense that the learner has complete choice in the information received. Specifically, we allow the learner to ask arbitrary yes/no questions. We consider both active learning under a fixed distribution and distributionfree active learning. In the case of active learning, the underlying probability distribution is used only to measure distance between concepts. For learnability with respect to a fixed distribution, active learning does not enlarge the set of learnable concept classes, but can improve the sample complexity. For distributionfree learning, it is shown that a concept class is actively learnable iff it is finite, so that active learning is in fact less powerful than the usual passive learning model. We also consider a form of distributionfree learning in which the learner knows the distribution being used, so that 'distributionfree' refers only to the requirement that a bound on the number of queries can be obtained uniformly over all distributions. Even with the side information of the distribution being used, a concept class is actively learnable iff it has finite VC dimension, so that active learning with the side information still does not enlarge the set of learnable concept classes
The informationbased complexity of dynamic programming
by CheeSeng Chow
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Book
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3 editions published in 1989 in English and held by 5 WorldCat member libraries worldwide
Efficient algorithms for globally optimal trajectories
by John N Tsitsiklis
(
Book
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3 editions published in 1993 in English and held by 5 WorldCat member libraries worldwide
Some properties of optimal thresholds in decentralized detection
by W. W Irving
(
Book
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3 editions published between 1991 and 1992 in English and held by 5 WorldCat member libraries worldwide
Complexity theoretic aspects of problems in control theory
by John N Tsitsiklis
(
Book
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3 editions published in 1993 in English and held by 5 WorldCat member libraries worldwide
Intractable problems in control theory
by Christos H Papadimitriou
(
Book
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1 edition published in 1984 in English and held by 5 WorldCat member libraries worldwide more
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Adaptive control systems Algorithms Artificial intelligence Computational complexity Computer network protocols Computer networks Control theory Detectors Dynamic programming Electronic data processingDistributed processing Graph theory Iterative methods (Mathematics) Learning Linear programming Markov processes Mathematical optimization Neural networks (Computer science) Operating systems (Computers) Operations research Parallel processing (Electronic computers) Probabilities Queuing theory Random variables Signal processingDigital techniques Stochastic approximation Stochastic processes System analysis Vector processing (Computer science)

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