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Electronic Colloquium on Computational Complexity

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REPORTS > KEYWORD > DECISION LISTS:
Reports tagged with Decision lists:
TR12-056 | 1st May 2012
Rocco Servedio, Li-Yang Tan, Justin Thaler

Attribute-Efficient Learning and Weight-Degree Tradeoffs for Polynomial Threshold Functions

Revisions: 1

We study the challenging problem of learning decision lists attribute-efficiently, giving both positive and negative results.

Our main positive result is a new tradeoff between the running time and mistake bound for learning length-$k$ decision lists over $n$ Boolean variables. When the allowed running time is relatively high, our new ... more >>>


TR19-007 | 17th January 2019
Arkadev Chattopadhyay, Meena Mahajan, Nikhil Mande, Nitin Saurabh

Lower Bounds for Linear Decision Lists

We demonstrate a lower bound technique for linear decision lists, which are decision lists where the queries are arbitrary linear threshold functions.
We use this technique to prove an explicit lower bound by showing that any linear decision list computing the function $MAJ \circ XOR$ requires size $2^{0.18 n}$. This ... more >>>


TR19-137 | 24th September 2019
Shachar Lovett, Kewen Wu, Jiapeng Zhang

Decision list compression by mild random restrictions

A decision list is an ordered list of rules. Each rule is specified by a term, which is a conjunction of literals, and a value. Given an input, the output of a decision list is the value corresponding to the first rule whole term is satisfied by the input. Decision ... more >>>




ISSN 1433-8092 | Imprint