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learn (11)
formula (5)
approxim (3)
use (3)
queri (3)

Stem dnf$ (all stems)

19 papers:

ICALPICALP-v1-2014-BlaisHST #approximate #on the
On DNF Approximators for Monotone Boolean Functions (EB, JH, RAS, LYT), pp. 235–246.
KDDKDD-2012-LiZ
Sampling minimal frequent boolean (DNF) patterns (GL, MJZ), pp. 87–95.
ICALPICALP-v1-2011-NordstromR #on the #satisfiability #trade-off
On Minimal Unsatisfiability and Time-Space Trade-offs for k-DNF Resolution (JN, AAR), pp. 642–653.
STOCSTOC-2009-Sellie #learning #random
Exact learning of random DNF over the uniform distribution (LS), pp. 45–54.
ICSTICST-2009-KaminskiA09a #fault #logic #mutation testing #performance #testing #using
Using a Fault Hierarchy to Improve the Efficiency of DNF Logic Mutation Testing (GKK, PA), pp. 386–395.
ICALPICALP-2007-ODonnellW #approximate
Approximation by DNF: Examples and Counterexamples (RO, KW), pp. 195–206.
STOCSTOC-2005-Alekhnovich #bound #random
Lower bounds for k-DNF resolution on random 3-CNFs (MA), pp. 251–256.
ICMLICML-2003-RuckertK #learning #probability
Stochastic Local Search in k-Term DNF Learning (UR, SK), pp. 648–655.
STOCSTOC-2002-HellersteinR #learning #using
Exact learning of DNF formulas using DNF hypotheses (LH, VR), pp. 465–473.
STOCSTOC-2001-KlivansS01a #learning
Learning DNF in time 2Õ(n1/3) (AK, RAS), pp. 258–265.
STOCSTOC-1996-BergadanoCV #learning #query
Learning Sat-k-DNF Formulas from Membership Queries (FB, DC, SV), pp. 126–130.
STOCSTOC-1996-Bshouty #towards
Towards the Learnability of DNF Formulae (NHB), pp. 131–140.
STOCSTOC-1994-BlumFJKMR #analysis #fourier #learning #query #statistics #using
Weakly learning DNF and characterizing statistical query learning using Fourier analysis (AB, MLF, JCJ, MJK, YM, SR), pp. 253–262.
ICMLICML-1993-NortonH #learning #probability
Learning DNF Via Probabilistic Evidence Combination (SWN, HH), pp. 220–227.
STOCSTOC-1992-BlumR #learning #performance #query
Fast Learning of k-Term DNF Formulas with Queries (AB, SR), pp. 382–389.
STOCSTOC-1991-LubyV #approximate #on the
On Deterministic Approximation of DNF (ML, BV), pp. 430–438.
ICMLML-1990-Kaelbling #learning
Learning Functions in k-DNF from Reinforcement (LPK), pp. 162–169.
ICMLML-1989-PagalloH #algorithm
Two Algorithms That Learn DNF by Discovering Relevant Features (GP, DH), pp. 119–123.
ICALPICALP-1988-KuceraMP #on the
On the Learnability of DNF Formulae (LK, AMS, MP), pp. 347–361.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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