Results 11  20
of
531
An analytic solution to discrete Bayesian reinforcement learning.
 In ICML.
, 2006
"... Abstract Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms come short of achieving this goal because the amount of exploration required is often too costly and/or too time ..."
Abstract

Cited by 139 (8 self)
 Add to MetaCart
, framing RL as a partially observable Markov decision process. Our two main contributions are the analytical derivation that the optimal value function is the upper envelope of a set of multivariate polynomials, and an efficient pointbased value iteration algorithm that exploits this simple
Energy Minimization for Linear Envelope MRFs
"... Markov random fields with higher order potentials have emerged as a powerful model for several problems in computer vision. In order to facilitate their use, we propose a new representation for higher order potentials as upper and lower envelopes of linear functions. Our representation concisely mod ..."
Abstract

Cited by 26 (8 self)
 Add to MetaCart
Markov random fields with higher order potentials have emerged as a powerful model for several problems in computer vision. In order to facilitate their use, we propose a new representation for higher order potentials as upper and lower envelopes of linear functions. Our representation concisely
The overlay of lower envelopes and its applications
, 1994
"... Abstract Let F and 9 be two collections of a total of n bivariate algebraic functions of constant maximum degree. The minimization diagrams of F, 9 are the planar maps obtained by the xyprojections of the lower envelopes of F, g, respectively. We show that the combinatorial complexity of the overl ..."
Abstract
 Add to MetaCart
of the overlay of the minimization diagrams of F and of 9 is O(n2+E), for any £, > O. This result has several applications: (i) a nearquadratic upper bound on the complexity of the region in 3space enclosed between the lower envelope of one such collection of functions and the upper envelope of another
The Overlay ofLower Envelopes and its Applications
, 1994
"... Let F and G be two collections of a total of n bivariate algebraic functions of constant maximum degree. The minimization diagrams of F, G are the planar maps obtained by the xyprojections of the lower envelopes of F, G, respectively. We show that the combinatorial complexity of the overlay of the ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
of the minimization diagrams of F and of G is O(n 2+ "), for any ">0. This result has several applications: (i) a nearquadratic upper bound on the complexity of the region in 3space enclosed between the lower envelope of one such collection of functions and the upper envelope of another
Detection of LSB Matching Steganography using the Envelope of Histogram
"... Abstract—As wellknown, it is hard to detect LSB matching steganography when cover images are scans of photographs, which usually have highfrequency noise. This paper proposes a novel steganalysis method for this issue by making use of the following two facts: One is the local maxima of an image hi ..."
Abstract
 Add to MetaCart
histogram decrease and the local minima increase after LSB matching steganography. As a result, the area between upper envelope and lower envelope of the histogram of a stego image will be smaller than that of a cover image. The other is LSB matching embedding in the spatial domain of an image corresponds
Convexity in HamiltonJacobi Theory 2: Envelope Representations
 SIAM J. Control and Optimization
, 2001
"... Abstract. Upper and lower envelope representations are developed for value functions associated with problems of optimal control and the calculus of variations that are fully convex, in the sense of exhibiting convexity in both the state and the velocity. Such convexity is used in dualizing the uppe ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
Abstract. Upper and lower envelope representations are developed for value functions associated with problems of optimal control and the calculus of variations that are fully convex, in the sense of exhibiting convexity in both the state and the velocity. Such convexity is used in dualizing
Detection of LSB Matching Steganography using the Envelope of Histogram
"... Abstract—As wellknown, it is hard to detect LSB matching steganography when cover images are scans of photographs, which usually have highfrequency noise. This paper proposes a novel steganalysis method for this issue by making use of the following two facts: One is the local maxima of an image hi ..."
Abstract
 Add to MetaCart
histogram decrease and the local minima increase after LSB matching steganography. As a result, the area between upper envelope and lower envelope of the histogram of a stego image will be smaller than that of a cover image. The other is LSB matching embedding in the spatial domain of an image corresponds
REACH ENVELOPE OF A 9DEGREEOFFREEDOM MODEL OF THE UPPER EXTREMITY
, 2005
"... This paper presents a rigorous mathematical formulation for modelling the upper extremity that is capable of considering a relatively large number of degrees of freedom, thus yielding a realistic model and associated envelope. Kinematic models are used to determine the reach envelope in closed form ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
This paper presents a rigorous mathematical formulation for modelling the upper extremity that is capable of considering a relatively large number of degrees of freedom, thus yielding a realistic model and associated envelope. Kinematic models are used to determine the reach envelope in closed
Families of Linear Functions and Their Envelopes
"... 2 (the upper branch of the hyperbola y 2 \Gamma x 2 = 1), i.e. the set of lines of the form y = ax + p 1 + a 2 . Figure 1 leads us to the conjecture that we may view this family of linear functions as the set of lines tangent to the graph of the upper half of the unit circle. In general we ..."
Abstract
 Add to MetaCart
2 (the upper branch of the hyperbola y 2 \Gamma x 2 = 1), i.e. the set of lines of the form y = ax + p 1 + a 2 . Figure 1 leads us to the conjecture that we may view this family of linear functions as the set of lines tangent to the graph of the upper half of the unit circle. In general we
Uncertainty Envelopes ∗ Yaron
"... We introduce a new class of problems: computing the set of all the convex combinations of sites when their position is uncertain and depends linearly on shared parameters which vary according to a uniform distribution. The boundary of the set, called the uncertainty envelope, is useful in optimizing ..."
Abstract
 Add to MetaCart
in optimizing processes where there is uncertainty on the site positions and the objective functions. We provide upper bounds on the combinatorial complexity of the uncertainty envelope, and present the first efficient algorithm for its computation in the general case. 1
Results 11  20
of
531