Often, several different algorithms can solve a certain practical problem. Sometimes, algorithms which are successful in solving one problem can solve other problems as well. How can we decide which of the original algorithms is the most promising -- i.e., which is more probable to be able to solve other problem? In many cases, the simplest algorithms turns out to be the most successful. In this paper, we provide a possible explanation for this empirical observation
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
For many years, artificial intelligence research has beenfocusing on inventing new algorithms and ap...
Results on human performance on the Traveling Salesman Problem (TSP) from different laboratories sho...
Often, several different algorithms can solve a certain practical prob-lem. Sometimes, algorithms wh...
We give some dos and don'ts for those analysing algorithms experimentally. We illustrate these ...
The choice of the right problem-solving method, from available methods, is a crucial skill for exper...
The last 30 years have seen enormous progress in the design of algorithms, but comparatively little ...
Most practical problems lead either to solving a system of equation or to optimization. From the com...
The M5 forecasting competition has provided strong empirical evidence that machine learning methods ...
Computer scientists always strive to find better and faster algorithms for any computational problem...
Research shows that evidence-based algorithms more accurately predict the future than do human forec...
To better understand why machine learning works, we cast learning problems as searches and character...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
Basic definition of algorithm in mathematics is step by step procedure to solve a problem. Algorithm...
The last twenty years have seen enormous progress in the design of algorithms, but little of it has ...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
For many years, artificial intelligence research has beenfocusing on inventing new algorithms and ap...
Results on human performance on the Traveling Salesman Problem (TSP) from different laboratories sho...
Often, several different algorithms can solve a certain practical prob-lem. Sometimes, algorithms wh...
We give some dos and don'ts for those analysing algorithms experimentally. We illustrate these ...
The choice of the right problem-solving method, from available methods, is a crucial skill for exper...
The last 30 years have seen enormous progress in the design of algorithms, but comparatively little ...
Most practical problems lead either to solving a system of equation or to optimization. From the com...
The M5 forecasting competition has provided strong empirical evidence that machine learning methods ...
Computer scientists always strive to find better and faster algorithms for any computational problem...
Research shows that evidence-based algorithms more accurately predict the future than do human forec...
To better understand why machine learning works, we cast learning problems as searches and character...
Heuristic algorithms are often difficult to analyse theoretically; this holds in particular for adva...
Basic definition of algorithm in mathematics is step by step procedure to solve a problem. Algorithm...
The last twenty years have seen enormous progress in the design of algorithms, but little of it has ...
Comparison of performance obtained by our approach with other state-of-the-art algorithms.</p
For many years, artificial intelligence research has beenfocusing on inventing new algorithms and ap...
Results on human performance on the Traveling Salesman Problem (TSP) from different laboratories sho...