u t c o r R esearch e p o r t
... values indicate less risky, i.e., more acceptable random outcomes. In the literature the opposite convention (where small values are preferred) is also widespread, especially when dealing with loss functions. When citing such sources, the definitions and formulas are altered to reflect this differen ...
... values indicate less risky, i.e., more acceptable random outcomes. In the literature the opposite convention (where small values are preferred) is also widespread, especially when dealing with loss functions. When citing such sources, the definitions and formulas are altered to reflect this differen ...
linear equations with boolean variables
... where ψa0 has the same expression as ψa but with ba = 0. Notice that µ0 is always well defined as a probability distribution, because the homogeneous systems has at least the solution x = 0, while µ is well defined only for SAT instances. The linear structure has several important consequences. • If ...
... where ψa0 has the same expression as ψa but with ba = 0. Notice that µ0 is always well defined as a probability distribution, because the homogeneous systems has at least the solution x = 0, while µ is well defined only for SAT instances. The linear structure has several important consequences. • If ...
Chapter 4. Method of Maximum Likelihood
... • The statistician may be a “pessimist” who does not believe in any particular model f (x, θ). In this case he must be satisfied with descriptive methods (like exploratory data analysis) without the possibility of inductive inference. • The statistician may be an “optimist” who strongly believes in ...
... • The statistician may be a “pessimist” who does not believe in any particular model f (x, θ). In this case he must be satisfied with descriptive methods (like exploratory data analysis) without the possibility of inductive inference. • The statistician may be an “optimist” who strongly believes in ...
Learning efficient Nash equilibria in distributed systems
... (2007).1 An essential feature of these rules is that players have two different search modes: (i) deliberate experimentation, which occurs with low probability and leads to a change of strategy only if it results in a higher payoff than the current aspiration level; (ii) random search, which leads t ...
... (2007).1 An essential feature of these rules is that players have two different search modes: (i) deliberate experimentation, which occurs with low probability and leads to a change of strategy only if it results in a higher payoff than the current aspiration level; (ii) random search, which leads t ...
The Bowling Scheme - at www.arxiv.org.
... Proof. It is natural to write the decision variable x in the convex program (2.2) relative to the true unknown: u := x − x ♮ . Using the expression (2.1) for the measurement vector y , we obtain the equivalent problem ...
... Proof. It is natural to write the decision variable x in the convex program (2.2) relative to the true unknown: u := x − x ♮ . Using the expression (2.1) for the measurement vector y , we obtain the equivalent problem ...
How to Built an Infinite Lottery Machine
... physical possibility. For we expect that inductive reasoning, like deductive reasoning, should be possible not just in worlds exactly like ours, but in any world that (a) can be described without logical contradiction (hence non-trivial deductive inference is possible) and (b) is governed by some re ...
... physical possibility. For we expect that inductive reasoning, like deductive reasoning, should be possible not just in worlds exactly like ours, but in any world that (a) can be described without logical contradiction (hence non-trivial deductive inference is possible) and (b) is governed by some re ...
Monte-Carlo Sampling for NP-Hard Maximization Problems in the
... 2. the best class (according to the real score) can be found on the basis of the approximated scores; 3. the sampling of classes may be achieved efficiently (polynomial time). For the sake of simplicity, let us first explain on a simple binary grammar what the sampling method consist of, although it ...
... 2. the best class (according to the real score) can be found on the basis of the approximated scores; 3. the sampling of classes may be achieved efficiently (polynomial time). For the sake of simplicity, let us first explain on a simple binary grammar what the sampling method consist of, although it ...
Conditional Degree of Belief - Philsci
... However, this probability is objective, but not ontic—it is no physical chance that describes properties of the real world (Rosenthal, 2004). It is not about the objective chance of an event E in a real experiment, nor about the long-run frequency of E. Instead, it describes the objective chance of ...
... However, this probability is objective, but not ontic—it is no physical chance that describes properties of the real world (Rosenthal, 2004). It is not about the objective chance of an event E in a real experiment, nor about the long-run frequency of E. Instead, it describes the objective chance of ...
Cloze but no cigar: The complex relationship between cloze, corpus,... subjective probabilities in language processing
... learning or processing biases in the a→b link — that is, biases in cloze responses might reflect actual errors or inefficiencies in language users’ predictions about upcoming material. Such errors would be of great theoretical interest, but have not previously been possible to study, since you canno ...
... learning or processing biases in the a→b link — that is, biases in cloze responses might reflect actual errors or inefficiencies in language users’ predictions about upcoming material. Such errors would be of great theoretical interest, but have not previously been possible to study, since you canno ...
1 1. Justification of analogical reasoning • an argument that it is
... Results obtained for one system can be transferred to the other (e.g., circuit model for a system of pipes). Assessment: The assumption of isomorphism transforms analogical inference into unproblematic deductive inference. But suitable only given very detailed background knowledge; cannot account fo ...
... Results obtained for one system can be transferred to the other (e.g., circuit model for a system of pipes). Assessment: The assumption of isomorphism transforms analogical inference into unproblematic deductive inference. But suitable only given very detailed background knowledge; cannot account fo ...
Performance Analysis of a Heterogeneous Traffic Scheduler
... Previously, large deviation theory was successfully applied to wireline networks as well as for channel state aware wireless scheduling algorithms. However, when applied to queue length aware wireless scheduling algorithms, this approach encounters a significant amount of technical difficulty. When ...
... Previously, large deviation theory was successfully applied to wireline networks as well as for channel state aware wireless scheduling algorithms. However, when applied to queue length aware wireless scheduling algorithms, this approach encounters a significant amount of technical difficulty. When ...
this one (Raghavendra, Schramm)
... This SDP solution assigns to each clique of size 1, . . . , d, a value that depends only on its size (in our case, d = 4). More formally, the SDP solution in [DM15] is specified by four parameters α = {αi }4i=1 as, M (G, α) = α|A∪B| · GA∪B , where for a set of vertices A ⊆ V , GA is the indicator th ...
... This SDP solution assigns to each clique of size 1, . . . , d, a value that depends only on its size (in our case, d = 4). More formally, the SDP solution in [DM15] is specified by four parameters α = {αi }4i=1 as, M (G, α) = α|A∪B| · GA∪B , where for a set of vertices A ⊆ V , GA is the indicator th ...
Probability box
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A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.