The Hardest Random SAT Problems
... A very interesting question is whether the constraint gap occurs with incomplete procedures which can only solve satis able problems. One such procedure is GSAT [13]. Although we have investigated this point experimentally, we have as yet failed to nd any strong evidence for variable behaviour or f ...
... A very interesting question is whether the constraint gap occurs with incomplete procedures which can only solve satis able problems. One such procedure is GSAT [13]. Although we have investigated this point experimentally, we have as yet failed to nd any strong evidence for variable behaviour or f ...
The problems in this booklet are organized into strands. A
... Step Right Up In a certain carnival game nine numbered paint cans are stacked as shown: ...
... Step Right Up In a certain carnival game nine numbered paint cans are stacked as shown: ...
Regular polygons - TTU Math Department
... Then DA = DM and CB = CM . So the triangles DAM and CBM are isosceles. It follows that ∠DAM = ∠DM A = 75◦, so M is the point from the statement of the problem. ...
... Then DA = DM and CB = CM . So the triangles DAM and CBM are isosceles. It follows that ∠DAM = ∠DM A = 75◦, so M is the point from the statement of the problem. ...
Time-Memory Trade-Off for Lattice Enumeration in a Ball
... Algorithm), a.k.a. Wagner algorithm. The input of the GBA algorithm is a list L0 of m = 2wr q n/w pairs (xi , ai )0≤i≤m−1 where xi is sampled as a Gaussian vector in the lattice generated by A with width s and ai = A−1 xi . The aim of this algorithm is to find a vector ...
... Algorithm), a.k.a. Wagner algorithm. The input of the GBA algorithm is a list L0 of m = 2wr q n/w pairs (xi , ai )0≤i≤m−1 where xi is sampled as a Gaussian vector in the lattice generated by A with width s and ai = A−1 xi . The aim of this algorithm is to find a vector ...
A polynomial time algorithm for Rayleigh ratio on
... function is then selected. This technique is called sweep and its use is justified by theoretical results in the form of approximability bounds, 4. In contrast, the technique proposed here solves optimally the discrete relaxation of the problem, ...
... function is then selected. This technique is called sweep and its use is justified by theoretical results in the form of approximability bounds, 4. In contrast, the technique proposed here solves optimally the discrete relaxation of the problem, ...
Quantile Regression for Large-scale Applications
... variable and observed covariates, and it is more appropriate in certain non-Gaussian settings. For these reasons, quantile regression has found applications in many areas (Buchinsky, 1994; Koenker & Hallock, 2001; Buhai, 2005). As with `1 regression, the quantile regression problem can be formulated ...
... variable and observed covariates, and it is more appropriate in certain non-Gaussian settings. For these reasons, quantile regression has found applications in many areas (Buchinsky, 1994; Koenker & Hallock, 2001; Buhai, 2005). As with `1 regression, the quantile regression problem can be formulated ...
Pdf - Text of NPTEL IIT Video Lectures
... series approximation. Thus, we can write f (X) can be approximated equal to f (X 1) plus del f (X 1) T (X minus X 1). Similarly, we can write g j (X) is equal to approximately equal to g (X 1), g j (X 1) plus grad of g j (X 1) T, (X minus X 1). Similarly, h k can be written in the similar manner tha ...
... series approximation. Thus, we can write f (X) can be approximated equal to f (X 1) plus del f (X 1) T (X minus X 1). Similarly, we can write g j (X) is equal to approximately equal to g (X 1), g j (X 1) plus grad of g j (X 1) T, (X minus X 1). Similarly, h k can be written in the similar manner tha ...
Seven Challenges in Parallel SAT Solving
... may be considered inferior to a solver that performs efficiently, even if its speedup figure is smaller. We expect this will be the case for many software and hardware verification applications in the near future, where limited size clusters are used to verify designs overnight. In the second catego ...
... may be considered inferior to a solver that performs efficiently, even if its speedup figure is smaller. We expect this will be the case for many software and hardware verification applications in the near future, where limited size clusters are used to verify designs overnight. In the second catego ...
Knapsack problem
The knapsack problem or rucksack problem is a problem in combinatorial optimization: Given a set of items, each with a mass and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items.The problem often arises in resource allocation where there are financial constraints and is studied in fields such as combinatorics, computer science, complexity theory, cryptography and applied mathematics.The knapsack problem has been studied for more than a century, with early works dating as far back as 1897. It is not known how the name ""knapsack problem"" originated, though the problem was referred to as such in the early works of mathematician Tobias Dantzig (1884–1956), suggesting that the name could have existed in folklore before a mathematical problem had been fully defined.