Stem varianc$ (all stems)

71 papers:

ICML-2015-BounliphoneGTB #consistency #dependence

A low variance consistent test of relative dependency (WB, AG, AT, MBB), pp. 20–29.

ICML-2015-HugginsNSM #markov #named #process

JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes (JHH, KN, AS, VKM), pp. 693–701.

ICML-2015-WangZ #clustering #named #parametricity

DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics (YW, JZ), pp. 862–870.

CASE-2014-ChiuC #bound #detection #image

A variance-reduction method for thyroid nodule boundary detection on ultrasound images (LYC, AC), pp. 681–685.

HCI-TMT-2014-LatoschikF #multimodal #reuse #scalability

Engineering Variance: Software Techniques for Scalable, Customizable, and Reusable Multimodal Processing (MEL, MF), pp. 308–319.

CIKM-2014-TaoW #performance #predict #query

Query Performance Prediction By Considering Score Magnitude and Variance Together (YT, SW), pp. 1891–1894.

CIKM-2014-ZhangHSWHH #evaluation

Generalized Bias-Variance Evaluation of TREC Participated Systems (PZ, LH, DS, JW, YH, BH), pp. 1911–1914.

POPL-2014-SharmaNA #program analysis #trade-off

Bias-variance tradeoffs in program analysis (RS, AVN, AA), pp. 127–138.

DHM-SET-2013-BrooksB #game studies #using #video

Facilitators’ Intervention Variance and Outcome Influence When Using Video Games with Fibromyalgia Patients (ALB, EPB), pp. 163–172.

HIMI-D-2013-KoedaKN #estimation

Relative Position Calibration between Two Haptic Devices Based on Minimum Variance Estimation (MK, YK, HN), pp. 72–79.

ICML-c1-2013-ChenWC

Maximum Variance Correction with Application to A* Search (WC, KQW, YC), pp. 302–310.

ICML-c3-2013-Cuturid

Mean Reversion with a Variance Threshold (MC, Ad), pp. 271–279.

ICML-c3-2013-TamarCM #difference

Temporal Difference Methods for the Variance of the Reward To Go (AT, DDC, SM), pp. 495–503.

SIGIR-2013-WhitingZJL #multi

Temporal variance of intents in multi-faceted event-driven information needs (SW, KZ, JMJ, ML), pp. 989–992.

SIGIR-2013-ZhangSWH #composition #evaluation #information retrieval

Bias-variance decomposition of ir evaluation (PZ, DS, JW, YH), pp. 1021–1024.

SAC-2013-CostaFLAV #metaheuristic #optimisation #statistics

Optimization metaheuristics for minimizing variance in a real-world statistical application (EC, FF, ARL, HA, FMV), pp. 206–207.

CIKM-2012-CaiZ #injection #learning #rank

Variance maximization via noise injection for active sampling in learning to rank (WC, YZ), pp. 1809–1813.

ICML-2012-CastroTM #policy

Policy Gradients with Variance Related Risk Criteria (DDC, AT, SM), p. 215.

ICML-2012-KolarS #estimation

Variance Function Estimation in High-dimensions (MK, JS), p. 115.

SIGIR-2012-RobertsonK #evaluation #information retrieval #on the #topic

On per-topic variance in IR evaluation (SER, EK), pp. 891–900.

ECOOP-2012-AltidorRS #java

Java Wildcards Meet Definition-Site Variance (JA, CR, YS), pp. 509–534.

SAC-2012-YuHJSLH #novel #programming #segmentation

A novel segmentation method for convex lesions based on dynamic programming with local intra-class variance (MY, QH, RJ, ES, HL, CCH), pp. 39–44.

PLDI-2011-AltidorHS

Taming the wildcards: combining definition- and use-site variance (JA, SSH, YS), pp. 602–613.

CIKM-2011-HsuC #analysis #component #independence #privacy

Privacy preservation by independent component analysis and variance control (CMH, MSC), pp. 925–930.

ECIR-2011-ZucconAR #analysis

Back to the Roots: Mean-Variance Analysis of Relevance Estimations (GZ, LA, KvR), pp. 716–720.

ICML-2011-MannorT #markov #optimisation #process

Mean-Variance Optimization in Markov Decision Processes (SM, JNT), pp. 177–184.

SIGIR-2011-GanjisaffarCL #modelling #precise #ranking

Bagging gradient-boosted trees for high precision, low variance ranking models (YG, RC, CVL), pp. 85–94.

DATE-2010-LiSBNO #analysis #implementation

Power Variance Analysis breaks a masked ASIC implementation of AES (YL, KS, LB, DN, KO), pp. 1059–1064.

SIGMOD-2010-ChaudhuriLN #optimisation #query

Variance aware optimization of parameterized queries (SC, HL, VRN), pp. 531–542.

VLDB-2010-SchadDQ #in the cloud #metric #runtime

Runtime Measurements in the Cloud: Observing, Analyzing, and Reducing Variance (JS, JD, JAQR), pp. 460–471.

ICML-2010-ThieryS #policy #problem #trade-off

Least-Squares Policy Iteration: Bias-Variance Trade-off in Control Problems (CT, BS), pp. 1071–1078.

ICPR-2010-Ramirez-OrtegonR #documentation #evaluation

Unsupervised Evaluation Methods Based on Local Gray-Intensity Variances for Binarization of Historical Documents (MARO, RR), pp. 2029–2032.

ICPR-2010-SmithW #analysis

A Bias-Variance Analysis of Bootstrapped Class-Separability Weighting for Error-Correcting Output Code Ensembles (RSS, TW), pp. 61–64.

ECIR-2009-Wang #analysis #documentation #information retrieval #ranking

Mean-Variance Analysis: A New Document Ranking Theory in Information Retrieval (JW0), pp. 4–16.

RecSys-2009-UmyarovT #estimation #modelling #rating #recommendation #using

Improving rating estimation in recommender systems using aggregation- and variance-based hierarchical models (AU, AT), pp. 37–44.

ICML-2008-LuPV #analysis #component #multi

Uncorrelated multilinear principal component analysis through successive variance maximization (HL, KNP, ANV), pp. 616–623.

ICPR-2008-LevadaMT #image #markov #modelling #on the #probability #random

On the asymptotic variances of Gaussian Markov Random Field model hyperparameters in stochastic image modeling (ALML, NDAM, AT), pp. 1–4.

ICPR-2008-PaclikLND #analysis #estimation #multi #using

Variance estimation for two-class and multi-class ROC analysis using operating point averaging (PP, CL, JN, RPWD), pp. 1–4.

RecSys-2008-Kwon #rating #recommendation #using

Improving top-n recommendation techniques using rating variance (YK), pp. 307–310.

PODS-2007-ZhangG #estimation

Variance estimation over sliding windows (LZ, YG), pp. 225–232.

CIAA-2007-GoldwurmR #modelling #statistics

Average Value and Variance of Pattern Statistics in Rational Models (MG, RR), pp. 62–72.

CIKM-2007-LiA #approach #clustering #multi #named #relational

Diva: a variance-based clustering approach for multi-type relational data (TL, SSA), pp. 147–156.

POPL-2007-BerdineCCDO #analysis

Variance analyses from invariance analyses (JB, AC, BC, DD, PWO), pp. 211–224.

TestCom-FATES-2007-VegaSD #quality #testing

Test Data Variance as a Test Quality Measure: Exemplified for TTCN-3 (DV, IS, GD), pp. 351–364.

CASE-2006-ChandrasekaranSPV #algorithm #optimisation #permutation #problem #scheduling

An Application of Particle Swarm Optimization Algorithm to Permutation Flowshop Scheduling Problems to Minimize Makespan, Total Flowtime and Completion Time Variance (SC, RKS, SGP, NV), pp. 513–518.

ICML-2006-LeeGW #classification #using

Using query-specific variance estimates to combine Bayesian classifiers (CHL, RG, SW), pp. 529–536.

ICPR-v1-2006-Chen #adaptation #estimation

Noise Variance Adaptive SEA for Motion Estimation: A Two-Stage Schema (WGC), pp. 31–34.

ICPR-v2-2006-LuB #image #nearest neighbour #performance #retrieval

Fast Image Retrieval Based on Equal-average Equal-variance K-Nearest Neighbour Search (ZML, HB), p. 853–?.

ICPR-v3-2006-KyanG #clustering #self

Local Variance Driven Self-Organization for Unsupervised Clustering (MJK, LG), pp. 421–424.

ICPR-v4-2006-ChaiWJZ #novel #recognition

A Novel Human Gait Recognition Method by Segmenting and Extracting the Region Variance Feature (YC, QW, JJ, RZ), pp. 425–428.

ECOOP-2006-EmirKRY #c# #constraints

Variance and Generalized Constraints for C^# Generics (BE, AK, CVR, DY), pp. 279–303.

DATE-2005-LiuFYO #analysis #correlation #graph #modelling

Hierarchical Variance Analysis for Analog Circuits Based on Graph Modelling and Correlation Loop Tracing (FL, JJF, DVY, SO), pp. 126–131.

SAC-2005-XiaPLCS

Indexing continuously changing data with mean-variance tree (YX, SP, SL, RC, RS), pp. 1125–1132.

LICS-2005-EsparzaKM #analysis #automaton #probability

Quantitative Analysis of Probabilistic Pushdown Automata: Expectations and Variances (JE, AK, RM), pp. 117–126.

STOC-2004-Feige #bound #graph #independence #on the #random

On sums of independent random variables with unbounded variance, and estimating the average degree in a graph (UF), pp. 594–603.

ICML-2004-MannorSST #bias #estimation

Bias and variance in value function estimation (SM, DS, PS, JNT).

ICPR-v1-2004-SirisathitkulAU #distance #image #performance #using

Fast Color Image Quantization using Squared Euclidean Distance of Adjacent Color Points along the Highest Color Variance Axis (YS, SA, BU), pp. 656–659.

PODS-2003-BabcockDMO #data type #maintenance

Maintaining variance and k-medians over data stream windows (BB, MD, RM, LO), pp. 234–243.

CIKM-2002-GreiffMP #information retrieval #probability

The role of variance in term weighting for probabilistic information retrieval (WRG, WTM, JMP), pp. 252–259.

ECOOP-2002-IgarashiV #on the #parametricity #type system

On Variance-Based Subtyping for Parametric Types (AI, MV), pp. 441–469.

ICML-2001-SatoK #learning #markov #problem

Average-Reward Reinforcement Learning for Variance Penalized Markov Decision Problems (MS, SK), pp. 473–480.

ICML-2000-Domingos00a #composition

A Unifeid Bias-Variance Decomposition and its Applications (PMD), pp. 231–238.

ICPR-v2-2000-HansenH #bias #composition #exponential #fault #independence #product line

General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of Distributions (JVH, TH), pp. 2207–2210.

SIGIR-2000-TakasuA #categorisation #classification #comparison

Variance based classifier comparison in text categorization (AT, KA), pp. 316–317.

CSMR-1999-KarhinenST #approach #legacy

An Approach to Manage Variance in Legacy Systems (AK, MS, JOT), pp. 190–193.

ICALP-1999-Woeginger

An FPTAS for Agreeably Weighted Variance on a Single Machine (GJW), pp. 707–716.

CIKM-1997-LeeC

Reducing Match Time Variance in Production Systems with HAL (PyL, AMKC), pp. 309–316.

ICML-1996-KahaviW #bias #composition

Bias Plus Variance Decomposition for Zero-One Loss Functions (RK, DW), pp. 275–283.

ICML-1995-KongD #bias

Error-Correcting Output Coding Corrects Bias and Variance (EBK, TGD), pp. 313–321.

DAC-1993-ChaiyakulGR

High-Level Transformations for Minimizing Syntactic Variances (VC, DG, LR), pp. 413–418.

PLDI-1989-Sarkar #execution

Determining Average Program Execution Times and their Variance (VS), pp. 298–312.