BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Used together with:
requir (3)
between (2)
algorithm (2)
declust (2)
estim (2)

Stem discrep$ (all stems)

13 papers:

ICALPICALP-v1-2015-FontesJKLLR #communication #complexity
Relative Discrepancy Does not Separate Information and Communication Complexity (LF, RJ, IK, SL, ML, JR), pp. 506–516.
KDDKDD-2015-CortesMM #adaptation #algorithm
Adaptation Algorithm and Theory Based on Generalized Discrepancy (CC, MM, AMM), pp. 169–178.
CIKMCIKM-2014-DongYMLSWWGY #multi #statistics
Maximizing Multi-scale Spatial Statistical Discrepancy (WD, RY, CM, CL, LS, LW, YW, PG, JY), pp. 471–480.
ICMLICML-c1-2014-IyerNS #bound #convergence #estimation #kernel
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection (AI, SN, SS), pp. 530–538.
ICSTSAT-2014-KonevL #satisfiability
A SAT Attack on the Erdős Discrepancy Conjecture (BK, AL), pp. 219–226.
Optimal private halfspace counting via discrepancy (SM, AN), pp. 1285–1292.
DATEDATE-2010-AlpaslanDKMHW #simulation
NIM- a noise index model to estimate delay discrepancies between silicon and simulation (EA, JD, BK, AKM, WMH, PvdW), pp. 1373–1376.
RERE-2003-DeraitusM #requirements #why
Customer Requirements and User Requirements: Why the Discrepancies (MD, AM), p. 279.
PODSPODS-2002-ChenC #clustering #multi #query
From Discrepancy to Declustering: Near optimal multidimensional declustering strategies for range queries (CMC, CTC), pp. 29–38.
ICALPICALP-2001-SadakaneTT #algorithm #combinator #sequence
Combinatorics and Algorithms on Low-Discrepancy Roundings of a Real Sequence (KS, NTC, TT), pp. 166–177.
SEKESEKE-2001-MorenoS #classification #detection #requirements
A Method for Detection, Classification and Resolution of Discrepancies in Viewpoint-based Requirements Engineering (AMM, AS), pp. 110–119.
SIGMODSIGMOD-1991-KrishnamurthyLK #database
Language Features for Interoperability of Databases with Schematic Discrepancies (RK, WL, WK), pp. 40–49.
STOCSTOC-1991-CoffmanCGJMSWY #analysis #case study
Fundamental Discrepancies between Average-Case Analyses under Discrete and Continuous Distributions: A Bin Packing Case Study (EGCJ, CC, MRG, DSJ, LAM, PWS, RRW, MY), pp. 230–240.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.