Lecture Slides (PowerPoint)
... Generating admissible heuristics The cost of an optimal solution to a relaxed problem is an admissible heuristic for the original problem. ...
... Generating admissible heuristics The cost of an optimal solution to a relaxed problem is an admissible heuristic for the original problem. ...
Rotamer Packing Problem - NUS School of Computing
... • This way, SCWRL manage to have the complexity to be bound by the size of the largest cycle in the residue connectivity graph. ...
... • This way, SCWRL manage to have the complexity to be bound by the size of the largest cycle in the residue connectivity graph. ...
Spatio-Temporal Reasoning and Context Awareness
... even healthy aging tends to be accompanied by at least some cognitive impairment (mainly involving memory problems and slowed processing speed). Third, there are people that suffer more than normal cognitive impairment for their age, usually involving dementia [29] (poor intellectual functioning inv ...
... even healthy aging tends to be accompanied by at least some cognitive impairment (mainly involving memory problems and slowed processing speed). Third, there are people that suffer more than normal cognitive impairment for their age, usually involving dementia [29] (poor intellectual functioning inv ...
Recursion Review - Department of Computer Science
... The height of the tree is closely related to the amount of memory that the program will require The total size of the tree reflects the number of times the key step will be done ...
... The height of the tree is closely related to the amount of memory that the program will require The total size of the tree reflects the number of times the key step will be done ...
Package `miRNAtap`
... It is a package with tools to facilitate implementation of workflows requiring miRNA prediction through access to multiple prediction results (DIANA, Targetscan, PicTar, Miranda, and miRDB) and their aggregation. Three aggregation methods are available: minimum, maximum and geometric mean, additiona ...
... It is a package with tools to facilitate implementation of workflows requiring miRNA prediction through access to multiple prediction results (DIANA, Targetscan, PicTar, Miranda, and miRDB) and their aggregation. Three aggregation methods are available: minimum, maximum and geometric mean, additiona ...
Quantifying the Slightly Deleterious Mutation Model of Molecular
... where u is the nucleotide mutation rate per site per generation. The level of divergence, k, for the sequence between two species is equal to 2tgu, where g is the number of generations per year and t is the time of divergence between sequences in the species in years: i.e., t 5 ts 1 2Na/g, where ts ...
... where u is the nucleotide mutation rate per site per generation. The level of divergence, k, for the sequence between two species is equal to 2tgu, where g is the number of generations per year and t is the time of divergence between sequences in the species in years: i.e., t 5 ts 1 2Na/g, where ts ...
Coding for Interactive Communication
... For this reason we will be concerned with the problem of achieving simultaneously high communication rate and high reliability, in arbitrary interactive protocols. Observe that in the case of an interactive protocol, the processors generally do not know what they want to transmit more than one bit a ...
... For this reason we will be concerned with the problem of achieving simultaneously high communication rate and high reliability, in arbitrary interactive protocols. Observe that in the case of an interactive protocol, the processors generally do not know what they want to transmit more than one bit a ...
Common Ancestry and Natural Selection
... genetic drift, not natural selection. Of course, Kimura’s theory is consistent with the Darwinian theory, if the former is restricted to molecular traits and the latter is restricted to morphological, physiological, and behavioural traits; when not restricted in this way, the two theories conflict. ...
... genetic drift, not natural selection. Of course, Kimura’s theory is consistent with the Darwinian theory, if the former is restricted to molecular traits and the latter is restricted to morphological, physiological, and behavioural traits; when not restricted in this way, the two theories conflict. ...
A Framework for Mining Sequential Patterns from Spatio
... pn : Number of maximal sequential patterns ps : Mean length of maximal sequential patterns costloadD : cost of loading data into main memory nSTS/ nSlicing-STS : number of times STS/Slicing-STS loads entire data into main memory ...
... pn : Number of maximal sequential patterns ps : Mean length of maximal sequential patterns costloadD : cost of loading data into main memory nSTS/ nSlicing-STS : number of times STS/Slicing-STS loads entire data into main memory ...
References - Gathering 4 Gardner
... As you have likely already realized, it is not always clear when a winning strategy exists and when it does not. The following theorem due to Baker and Norine, appearing in [1], gives a partial answer to this question. Theorem 0.1. For a given graph, let E be the number of edges and N be the number ...
... As you have likely already realized, it is not always clear when a winning strategy exists and when it does not. The following theorem due to Baker and Norine, appearing in [1], gives a partial answer to this question. Theorem 0.1. For a given graph, let E be the number of edges and N be the number ...
Bioinformatics with basic local alignment search tool (BLAST) and
... Pairwise sequence alignment can only be used between two sequences at a time. Multiple sequence alignment is an extension of pairwise alignment incorporating more than two sequences at a time. A structural sequence alignment analyzes the whole structure of a protein strand, unlike pairwise and multi ...
... Pairwise sequence alignment can only be used between two sequences at a time. Multiple sequence alignment is an extension of pairwise alignment incorporating more than two sequences at a time. A structural sequence alignment analyzes the whole structure of a protein strand, unlike pairwise and multi ...
Data Splitting
... represented by a finite training dataset T of examples of inputs and the corresponding desired outputs: T = { [ ~x1 , d~1 ], . . . , [ ~xn , d~n ] }, where n > 0 is the number of ordered pairs of input/output samples (patterns). At the end of the training process, the final model should predict corr ...
... represented by a finite training dataset T of examples of inputs and the corresponding desired outputs: T = { [ ~x1 , d~1 ], . . . , [ ~xn , d~n ] }, where n > 0 is the number of ordered pairs of input/output samples (patterns). At the end of the training process, the final model should predict corr ...
573 lecture 2
... What is Search? Search is a class of techniques for systematically finding or constructing solutions to problems. Example technique: generate-and-test. Example problem: Combination lock. 1. Generate a possible solution. 2. Test the solution. 3. If solution found THEN done ELSE return to step 1. © D ...
... What is Search? Search is a class of techniques for systematically finding or constructing solutions to problems. Example technique: generate-and-test. Example problem: Combination lock. 1. Generate a possible solution. 2. Test the solution. 3. If solution found THEN done ELSE return to step 1. © D ...
WPEssink CARV 2013 V4.2
... points required to describe the part accurately will increase. Therefore to account for this the techniques used to generate toolpaths for these parts will also become more complex. Genetic algorithms are a very efficient method of converging on a solution where there are a very large number of poss ...
... points required to describe the part accurately will increase. Therefore to account for this the techniques used to generate toolpaths for these parts will also become more complex. Genetic algorithms are a very efficient method of converging on a solution where there are a very large number of poss ...
PDF
... his bets. To formalize, suppose we have three variables Bet that can take the values odd and even, Dice that can take the values W45@@@57¢ , and £p 6¤ that can be either yes or no. Suppose also that we observe that the player won, that is Win P yes. Clearly, the likelihood " + Win P yes 1 Dice d ...
... his bets. To formalize, suppose we have three variables Bet that can take the values odd and even, Dice that can take the values W45@@@57¢ , and £p 6¤ that can be either yes or no. Suppose also that we observe that the player won, that is Win P yes. Clearly, the likelihood " + Win P yes 1 Dice d ...
Tutorial "Computational intelligence for data mining"
... • Gradient optimization works for large number of parameters. • Parameters sx are known for some features, use them as optimization parameters for others! • Probabilities instead of 0/1 rule outcomes. • Vectors that were not classified by crisp rules have now nonzero probabilities. ...
... • Gradient optimization works for large number of parameters. • Parameters sx are known for some features, use them as optimization parameters for others! • Probabilities instead of 0/1 rule outcomes. • Vectors that were not classified by crisp rules have now nonzero probabilities. ...
Lecture 6
... • Robustness to changing loss functions. Both generative and conditional probability models allow the loss function to be changed at run time without re-learning. Perceptron requires re-training the classifier when the loss function changes. • Robustness to model assumptions. The generative model us ...
... • Robustness to changing loss functions. Both generative and conditional probability models allow the loss function to be changed at run time without re-learning. Perceptron requires re-training the classifier when the loss function changes. • Robustness to model assumptions. The generative model us ...
Indexing and Searching Video Sequences Using Concept Lattices
... Once Q is given, it has to be classified in the concept lattice L(C) using the incremental classification algorithm of Godin et al. [8]. The resulting concept lattice is noted (C ⊕ Q, ⊑) where C ⊕ Q represents the new set of concepts once the query has been added. In the following, the concept latti ...
... Once Q is given, it has to be classified in the concept lattice L(C) using the incremental classification algorithm of Godin et al. [8]. The resulting concept lattice is noted (C ⊕ Q, ⊑) where C ⊕ Q represents the new set of concepts once the query has been added. In the following, the concept latti ...
User Manual of ClusterProject
... The column of Rep is indispensable whether the experiment has replication or not. If there is no replication, all values of this column are set to one. It can have additional factors in the input file such as dye, treatment or array et al. This is tab-delimited text file. Mixed model approaches are ...
... The column of Rep is indispensable whether the experiment has replication or not. If there is no replication, all values of this column are set to one. It can have additional factors in the input file such as dye, treatment or array et al. This is tab-delimited text file. Mixed model approaches are ...