Stem dnf$ (all stems)

19 papers:

ICALP-v1-2014-BlaisHST #approximate #on the

On DNF Approximators for Monotone Boolean Functions (EB, JH, RAS, LYT), pp. 235–246.

KDD-2012-LiZ

Sampling minimal frequent boolean (DNF) patterns (GL, MJZ), pp. 87–95.

ICALP-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.

STOC-2009-Sellie #learning #random

Exact learning of random DNF over the uniform distribution (LS), pp. 45–54.

ICST-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.

ICALP-2007-ODonnellW #approximate

Approximation by DNF: Examples and Counterexamples (RO, KW), pp. 195–206.

STOC-2005-Alekhnovich #bound #random

Lower bounds for k-DNF resolution on random 3-CNFs (MA), pp. 251–256.

ICML-2003-RuckertK #learning #probability

Stochastic Local Search in k-Term DNF Learning (UR, SK), pp. 648–655.

STOC-2002-HellersteinR #learning #using

Exact learning of DNF formulas using DNF hypotheses (LH, VR), pp. 465–473.

STOC-2001-KlivansS01a #learning

Learning DNF in time 2Õ(n1/3) (AK, RAS), pp. 258–265.

STOC-1996-BergadanoCV #learning #query

Learning Sat-k-DNF Formulas from Membership Queries (FB, DC, SV), pp. 126–130.

STOC-1996-Bshouty #towards

Towards the Learnability of DNF Formulae (NHB), pp. 131–140.

STOC-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.

ICML-1993-NortonH #learning #probability

Learning DNF Via Probabilistic Evidence Combination (SWN, HH), pp. 220–227.

STOC-1992-BlumR #learning #performance #query

Fast Learning of k-Term DNF Formulas with Queries (AB, SR), pp. 382–389.

STOC-1991-LubyV #approximate #on the

On Deterministic Approximation of DNF (ML, BV), pp. 430–438.

ML-1990-Kaelbling #learning

Learning Functions in k-DNF from Reinforcement (LPK), pp. 162–169.

ML-1989-PagalloH #algorithm

Two Algorithms That Learn DNF by Discovering Relevant Features (GP, DH), pp. 119–123.

ICALP-1988-KuceraMP #on the

On the Learnability of DNF Formulae (LK, AMS, MP), pp. 347–361.