Searching for "Random Descent." – sorted by Relevance.
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Perceptron learning with random coordinate descent
- Perceptron Learning with Random Coordinate Descent Ling Li Learning Systems Group, California
- Cited by 6 (3 self) – Add To MetaCart
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An Investigation Of Variable Neighbourhood Search For University Course Timetabling
- with an exponential monte carlo acceptance criteria. This heuristic search approach is based on random-descent local
- Cited by 6 (4 self) – Add To MetaCart
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The shape of the processor design space and its implications for early stage explorations
- studies. Four design space search algorithms (random descent, steepest descent, one
- Cited by 4 (0 self) – Add To MetaCart
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A Probabilistic Roadmap Approach for Systems with Closed Kinematic Chains
- randomized gradient descent to force satisfaction of the closure constraints. We gen- erate edges
- Cited by 57 (4 self) – Add To MetaCart
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A Memetic Algorithm for University Exam Timetabling
- the value of combining local search with the mutation operators in a population a multistart random descent
- Cited by 65 (20 self) – Add To MetaCart
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Automated operation minimization of tensor contraction expressions in electronic structure calculations
- . The best algorithm is found to be a random-descent heuristic, which is then used to explore the generated
- Cited by 1 (1 self) – Add To MetaCart
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A Parameter-Free Hyperheuristic for Scheduling a Sales Summit
- neighbourhood at random and applies it once (single call). RandomDescent chooses one neighbourhood at random
- Cited by 18 (9 self) – Add To MetaCart
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A Parameter-Free Hyperheuristic for Scheduling a Sales Summit
- neighbourhood at random and applies it once (single call). RandomDescent chooses one neighbourhood at random
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Efficient design space exploration of high performance embedded outof-order processors
- in the context of electronic design, such as random descent, steepest descent (hill climbing) [14], one
- Cited by 8 (1 self) – Add To MetaCart
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An experimental study on hyper-heuristics and exam timetabling
- mechanism chooses a low level heuristic at a time randomly. Random Descent mechanism chooses a low level
- Cited by 3 (0 self) – Add To MetaCart

