Optimal Conditioning of Quasi-Newton Methods
... included the straight Fletcher-Powell and Barnes-Rosen [1], [5] techniques, they are not included here. Previous tests have shown both to be substantially inferior to four of the five methods tested here. The results of the tests are summarized in Table 1. As in [6], Iter. designates the number of t ...
... included the straight Fletcher-Powell and Barnes-Rosen [1], [5] techniques, they are not included here. Previous tests have shown both to be substantially inferior to four of the five methods tested here. The results of the tests are summarized in Table 1. As in [6], Iter. designates the number of t ...
Inference with Minimal Communication: a Decision-Theoretic Variational Approach
... Assuming communication constraints are severe, we examine the extent to which alternative processing rules can avoid a loss in (MAP or MPM) performance. Specifically, given a directed graphical model with binary-valued hidden variables and real-valued noisy observations, we assume each node may broa ...
... Assuming communication constraints are severe, we examine the extent to which alternative processing rules can avoid a loss in (MAP or MPM) performance. Specifically, given a directed graphical model with binary-valued hidden variables and real-valued noisy observations, we assume each node may broa ...
IOSR Journal of Mathematics (IOSR-JM)
... The finite capacity of unit-II is expressed by the restriction. There can never be more the k+1 IIcustomers in the system. Whenever the number of II-Customers reaches K+1 we say that the system blocks. The service mechanism in II may be different depending on whether Unit-I is blocked or not. The de ...
... The finite capacity of unit-II is expressed by the restriction. There can never be more the k+1 IIcustomers in the system. Whenever the number of II-Customers reaches K+1 we say that the system blocks. The service mechanism in II may be different depending on whether Unit-I is blocked or not. The de ...
Homework 4: Solutions
... x has a data eld, and pointers next(x) and previous(x) to the next and previous nodes in the list, respectively. A special node h is called the head of the list; for this node the data eld is void and only the next(h) and previous(h) elds are used to point out the rst and last elements of the li ...
... x has a data eld, and pointers next(x) and previous(x) to the next and previous nodes in the list, respectively. A special node h is called the head of the list; for this node the data eld is void and only the next(h) and previous(h) elds are used to point out the rst and last elements of the li ...
Document
... minimizes is the most efficient estimator of alpha among all estimators based on a resampling of x. ...
... minimizes is the most efficient estimator of alpha among all estimators based on a resampling of x. ...
On the Complexity of Fixed-Size Bit
... In this section we discuss the complexity of deciding the bit-vector logics defined so far. We first summarize our results, and then give more detailed proofs for the new non-trivial ones. The results are also summarized in a tabular form in Appendix A. First, consider unary encoding of bit-widths. ...
... In this section we discuss the complexity of deciding the bit-vector logics defined so far. We first summarize our results, and then give more detailed proofs for the new non-trivial ones. The results are also summarized in a tabular form in Appendix A. First, consider unary encoding of bit-widths. ...
Slides
... over wireless networks: delay sensitivity analysis and simulations,” in Proceedings of the 16th IFAC World Congress, 2005. ...
... over wireless networks: delay sensitivity analysis and simulations,” in Proceedings of the 16th IFAC World Congress, 2005. ...
The average cost optimality equation
... stochastic kernel on X given K, and the one-step cost C is a measurable function on K. We denote by F the class of all Borel measurable functions f : X → A satisfying the constraint f (x) ∈ A(x) for each x ∈ X. A control policy π = {πt } is a sequence of rules to chose admissible controls, that is, ...
... stochastic kernel on X given K, and the one-step cost C is a measurable function on K. We denote by F the class of all Borel measurable functions f : X → A satisfying the constraint f (x) ∈ A(x) for each x ∈ X. A control policy π = {πt } is a sequence of rules to chose admissible controls, that is, ...
The Robustness-Performance Tradeoff in Markov Decision Processes
... the row-wise independent case. In robust MDP problems, there may be two different types of parameter uncertainty, namely, the reward uncertainty and the transition probability uncertainty. Under the assumption that the uncertainty is state-wise independent (an assumption made by all papers to date, ...
... the row-wise independent case. In robust MDP problems, there may be two different types of parameter uncertainty, namely, the reward uncertainty and the transition probability uncertainty. Under the assumption that the uncertainty is state-wise independent (an assumption made by all papers to date, ...
A HyFlex Module for the MAX-SAT Problem
... results in the whole formula evaluating to true. If there is such an assignment then the formula is said to be satisfiable, and if not then it is unsatisfiable. We consider here one of its related optimisation problems, the maximum satisfiability problem (MAX-SAT), in which the objective is to find ...
... results in the whole formula evaluating to true. If there is such an assignment then the formula is said to be satisfiable, and if not then it is unsatisfiable. We consider here one of its related optimisation problems, the maximum satisfiability problem (MAX-SAT), in which the objective is to find ...
Learning Algorithms for Separable Approximations of
... In this paper, we introduce and formally study the use of sequences of piecewise linear, separable approximations as a strategy for solving nondifferentiable stochastic optimization problems. As a byproduct, we produce a fast algorithm for problems such as two stage stochastic programs with network ...
... In this paper, we introduce and formally study the use of sequences of piecewise linear, separable approximations as a strategy for solving nondifferentiable stochastic optimization problems. As a byproduct, we produce a fast algorithm for problems such as two stage stochastic programs with network ...
Document
... *This work was supported in part by Office of Naval Research (ONR) "MINUTEMAN“ project under contract N00014-01-C-0016 and TRW under a Graduate Student Fellowship *This research was supported in part by the National Natural Science Foundation of China (NSFC) under ...
... *This work was supported in part by Office of Naval Research (ONR) "MINUTEMAN“ project under contract N00014-01-C-0016 and TRW under a Graduate Student Fellowship *This research was supported in part by the National Natural Science Foundation of China (NSFC) under ...
Notes - Mathematics
... 2. Patterns can be described by recursive (iterative) formulas and explicit (closed) formulas. Sometimes one is easier to recognize than the other. 3. Formulas can be recognized and justified by a variety of methods; e.g., algebraically, geometrically, using finite differences, using curve-fitting. ...
... 2. Patterns can be described by recursive (iterative) formulas and explicit (closed) formulas. Sometimes one is easier to recognize than the other. 3. Formulas can be recognized and justified by a variety of methods; e.g., algebraically, geometrically, using finite differences, using curve-fitting. ...
pdf
... kernel (regular conditional probability) from X to Y, such that Q( · |x) is a probability measure on the (Borel) σ-algebra B(Y) on Y for every x ∈ X, and Q(A| · ) : X → [0, 1] is a Borel measurable function for every A ∈ B(Y). Throughout the paper we let Q denote the set of all stochastic kernels fr ...
... kernel (regular conditional probability) from X to Y, such that Q( · |x) is a probability measure on the (Borel) σ-algebra B(Y) on Y for every x ∈ X, and Q(A| · ) : X → [0, 1] is a Borel measurable function for every A ∈ B(Y). Throughout the paper we let Q denote the set of all stochastic kernels fr ...
PDF
... importantly limited buffer space. Most probably reactive routing protocols are used for transfer of information. In this route to the destination is created only after demand from source, till that time packets are queued in buffer and transferred on priority basis. Day by day growth of internet is ...
... importantly limited buffer space. Most probably reactive routing protocols are used for transfer of information. In this route to the destination is created only after demand from source, till that time packets are queued in buffer and transferred on priority basis. Day by day growth of internet is ...
Optimization of (s, S) Inventory Systems with Random Lead Times
... that S ? s 1:50D . While Schneider and Ringuest suggest alternative schemes when this condition is violated, Tijms and Groenevelt speci cally mention that their approximations are not warranted when this condition is violated. For example, if we arbitrarily x the setup cost K = 36, and the per p ...
... that S ? s 1:50D . While Schneider and Ringuest suggest alternative schemes when this condition is violated, Tijms and Groenevelt speci cally mention that their approximations are not warranted when this condition is violated. For example, if we arbitrarily x the setup cost K = 36, and the per p ...
Cost-based placement of vDPI functions in NFV infrastructures
... part (and possibly also the header) of a packet flow, identifying traffic types, searching for protocol noncompliance, viruses, spam, intrusions, or any defined criteria. Originally implemented as hardware middleboxes to be installed in network infrastructures, DPI are evolving towards the Network F ...
... part (and possibly also the header) of a packet flow, identifying traffic types, searching for protocol noncompliance, viruses, spam, intrusions, or any defined criteria. Originally implemented as hardware middleboxes to be installed in network infrastructures, DPI are evolving towards the Network F ...
L10: k-Means Clustering
... estimate of centers, run on full set (will hopefully be close to converged). • Run a one-pass algorithm (streaming, covered later) getting O(k log k) clusters. Reduce to k clusters at end, but merging extra clusters. Can use another streaming trick where there are a hierarchy of clusters of recent s ...
... estimate of centers, run on full set (will hopefully be close to converged). • Run a one-pass algorithm (streaming, covered later) getting O(k log k) clusters. Reduce to k clusters at end, but merging extra clusters. Can use another streaming trick where there are a hierarchy of clusters of recent s ...
PDF
... instances (all with less than 28 variables) from the MAXSAT2007 competition benchmark, which are encodings of three classes of problems (Ramsey Problems, Spin Glasses, and Max Cliques). The true density is computed by exact enumeration. Our experiments show that the estimate is accurate and that the ...
... instances (all with less than 28 variables) from the MAXSAT2007 competition benchmark, which are encodings of three classes of problems (Ramsey Problems, Spin Glasses, and Max Cliques). The true density is computed by exact enumeration. Our experiments show that the estimate is accurate and that the ...
error-free
... tagged with virtual service start time Si,n and finish time fi,n Si,n = max{v(A(t)), fi,n-1} fi,n = Si,n + Li,n/ri Li,n : packet size of the arrived packet V(A(t)) : system virtual time defined in WFQ ri : service rate allocated to flow ...
... tagged with virtual service start time Si,n and finish time fi,n Si,n = max{v(A(t)), fi,n-1} fi,n = Si,n + Li,n/ri Li,n : packet size of the arrived packet V(A(t)) : system virtual time defined in WFQ ri : service rate allocated to flow ...
Vidhatha Technologies
... control, we can tightly control the number of packets inside the network. Second, by using arate-based scheduling algorithm with the computed virtual rate as input to schedule packets, we do not need to wait for the packets to accumulate before making scheduling decisions. However, the key difficult ...
... control, we can tightly control the number of packets inside the network. Second, by using arate-based scheduling algorithm with the computed virtual rate as input to schedule packets, we do not need to wait for the packets to accumulate before making scheduling decisions. However, the key difficult ...
Absolute o(logm) error in approximating random set covering: an
... steps. At each step a subset is selected. Each of the first k0 steps corresponds to selection of an arbitrary subset, whereas each of the subsequent steps (within the while loop) corresponds to selection of a subset covering a specific ground element. Let k ∈ {1, . . . , m} denote the kth selected s ...
... steps. At each step a subset is selected. Each of the first k0 steps corresponds to selection of an arbitrary subset, whereas each of the subsequent steps (within the while loop) corresponds to selection of a subset covering a specific ground element. Let k ∈ {1, . . . , m} denote the kth selected s ...
Exact MAP Estimates by (Hyper)tree Agreement
... \ h i e f g oi \e m g \ K _ pq E r%'&P 1` 2` \ (1b) where the indicator function i e f g is equal to one if $% , and zero otherwise. In this E %s ) tu E %`v with the case, the index set : consists of the union of : ...
... \ h i e f g oi \e m g \ K _ pq E r%'&P 1` 2` \ (1b) where the indicator function i e f g is equal to one if $% , and zero otherwise. In this E %s ) tu E %`v with the case, the index set : consists of the union of : ...