We give a poly(log(n),1/epsilon)-query adaptive algorithm for testing whether an unknown Boolean function f:{-1, 1}^n -> {-1, 1}, which is promised to be a halfspace, is monotone versus epsilon-far from monotone. Since non-adaptive algorithms are known to require almost Omega(n^{1/2}) queries to test whether an unknown halfspace is monotone versus far from monotone, this shows that adaptivity enables an exponential improvement in the query complexity of monotonicity testing for halfspaces.
@InProceedings{chen_et_al:LIPIcs.APPROX-RANDOM.2017.38, author = {Chen, Xi and Servedio, Rocco A. and Tan, Li-Yang and Waingarten, Erik}, title = {{Adaptivity Is Exponentially Powerful for Testing Monotonicity of Halfspaces}}, booktitle = {Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2017)}, pages = {38:1--38:21}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-044-6}, ISSN = {1868-8969}, year = {2017}, volume = {81}, editor = {Jansen, Klaus and Rolim, Jos\'{e} D. P. and Williamson, David P. and Vempala, Santosh S.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2017.38}, URN = {urn:nbn:de:0030-drops-75877}, doi = {10.4230/LIPIcs.APPROX-RANDOM.2017.38}, annote = {Keywords: property testing, linear threshold functions, monotonicity, adaptivity} }
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