bias

---

bias

Tag #bias

142 papers:

EDM-2019-OliveiraM #identification #performance #student

Identifying bias and underlying knowledge structures in Brazilian National Exam of Students Performance (MSO, CEM).

CoG-2019-ChristiansenGW #game studies #using

Resolving Simultaneity Bias: Using Features to Estimate Causal Effects in Competitive Games (AHC, EG, BSW), pp. 1–8.

CIKM-2019-ChenAJC #recommendation

Correcting for Recency Bias in Job Recommendation (RCC, QA, GJ, WBC), pp. 2185–2188.

CIKM-2019-WangGLML #on the #testing

On Heavy-user Bias in A/B Testing (YW, SG, JL, AM, SL), pp. 2425–2428.

ECIR-p1-2019-BorattoFM #algorithm #online #recommendation

The Effect of Algorithmic Bias on Recommender Systems for Massive Open Online Courses (LB, GF, MM), pp. 457–472.

ICML-2019-BrunetAAZ #comprehension #word

Understanding the Origins of Bias in Word Embeddings (MEB, CAH, AA, RSZ), pp. 803–811.

ICML-2019-RahamanBADLHBC #network #on the

On the Spectral Bias of Neural Networks (NR, AB, DA, FD, ML, FAH, YB, ACC), pp. 5301–5310.

ICML-2019-ShahGAD #learning #on the

On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference (RS, NG, PA, ADD), pp. 5670–5679.

ICML-2019-WangZB #matter #network

Bias Also Matters: Bias Attribution for Deep Neural Network Explanation (SW, TZ, JAB), pp. 6659–6667.

KDD-2019-Eliassi-RadCL #network

Incompleteness in Networks: Biases, Skewed Results, and Some Solutions (TER, RSC, TL), pp. 3217–3218.

ICSE-2019-ImtiazMCRBM #gender #git

Investigating the effects of gender bias on GitHub (NI, JM, JC, NR, GB, ERMH), pp. 700–711.

ICST-2019-LiuKB0KT #automation #benchmark #exclamation #fault #locality #metric #program repair #what

You Cannot Fix What You Cannot Find! An Investigation of Fault Localization Bias in Benchmarking Automated Program Repair Systems (KL0, AK, TFB, DK0, JK, YLT), pp. 102–113.

JCDL-2018-TraubSOH #crowdsourcing

Impact of Crowdsourcing OCR Improvements on Retrievability Bias (MCT, TS, JvO, LH), pp. 29–36.

CIKM-2018-ChandarC

Estimating Clickthrough Bias in the Cascade Model (PC, BC), pp. 1587–1590.

ICML-2018-GunasekarLSS #geometry #optimisation

Characterizing Implicit Bias in Terms of Optimization Geometry (SG, JDL, DS, NS), pp. 1827–1836.

ICML-2018-LiGD #induction #learning #network

Explicit Inductive Bias for Transfer Learning with Convolutional Networks (XL0, YG, FD), pp. 2830–2839.

ICML-2018-MianjyAV #on the

On the Implicit Bias of Dropout (PM, RA, RV), pp. 3537–3545.

ICML-2018-NeelR #adaptation #difference #privacy

Mitigating Bias in Adaptive Data Gathering via Differential Privacy (SN, AR0), pp. 3717–3726.

KDD-2018-LeeS #estimation #online

Winner's Curse: Bias Estimation for Total Effects of Features in Online Controlled Experiments (MRL, MS), pp. 491–499.

ECSA-2017-ZalewskiBR #architecture #on the

On Cognitive Biases in Architecture Decision Making (AZ, KB, AR), pp. 123–137.

CIKM-2017-ChenAS #analysis #empirical #performance

An Empirical Analysis of Pruning Techniques: Performance, Retrievability and Bias (RCC, LA, FS), pp. 2023–2026.

CIKM-2017-WilkieA #algorithm #documentation #question

Algorithmic Bias: Do Good Systems Make Relevant Documents More Retrievable? (CW, LA), pp. 2375–2378.

ICML-2017-RitterBSB #case study #network

Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study (SR, DGTB, AS, MMB), pp. 2940–2949.

KDD-2017-ZhengGNOY

Resolving the Bias in Electronic Medical Records (KZ, JG, KYN, BCO, JWLY), pp. 2171–2180.

OOPSLA-2017-WoodCBG #concurrent #detection

Instrumentation bias for dynamic data race detection (BPW, MC, MDB, DG), p. 31.

CASE-2017-ZhangJ #distributed #metric #network

Target tracking over distributed sensor networks by polar measurements with time-varying bias (CZ, YJ), pp. 429–433.

JCDL-2016-TraubSOHVH #assessment #corpus #scalability

Querylog-based Assessment of Retrievability Bias in a Large Newspaper Corpus (MCT, TS, JvO, JH, APdV, LH), pp. 7–16.

ECIR-2016-LipaniLH

The Curious Incidence of Bias Corrections in the Pool (AL, ML, AH), pp. 267–279.

ICML-2016-SaRO #agile

Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling (CDS, CR, KO), pp. 1567–1576.

KDD-2016-HajianBC #algorithm #data mining #mining

Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining (SH, FB, CC0), pp. 2125–2126.

HT-2015-DallmannLZH #online

Media Bias in German Online Newspapers (AD, FL, DZ, AH), pp. 133–137.

HT-2015-Graells-Garrido #gender #wiki #women

First Women, Second Sex: Gender Bias in Wikipedia (EGG, ML, FM), pp. 165–174.

ICSME-2015-PiorkowskiFSBKH #debugging #developer #how #information management

To fix or to learn? How production bias affects developers’ information foraging during debugging (DP, SDF, CS, MMB, IK, AZH, JM, CH, AH), pp. 11–20.

DiGRA-2015-BartonSQMKK #design #game studies #reduction #using

The Use of Theory in Designing a Serious Game for the Reduction of Cognitive Biases (MB, CS, MMQ, CKM, KSK, JK).

CHI-2015-Otterbacher #crowdsourcing #metadata

Crowdsourcing Stereotypes: Linguistic Bias in Metadata Generated via GWAP (JO), pp. 1955–1964.

CHI-2015-Ruiz0 #constraints #elicitation #gesture #legacy #performance

Soft-Constraints to Reduce Legacy and Performance Bias to Elicit Whole-body Gestures with Low Arm Fatigue (JR, DV), pp. 3347–3350.

CHI-2015-ZhangBK #design #information management

Designing Information for Remediating Cognitive Biases in Decision-Making (YZ, RKEB, WAK), pp. 2211–2220.

CSCW-2015-QuattroneCM #dataset

There’s No Such Thing as the Perfect Map: Quantifying Bias in Spatial Crowd-sourcing Datasets (GQ, LC, PDM), pp. 1021–1032.

HCI-UC-2015-Fraoua #information management

Moral Biases and Decision: Impact of Information System on Moral Biases (KEF), pp. 291–302.

CIKM-2015-LuCN #lightweight #named #social #social media #topic

BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media (HL, JC, WN), pp. 213–222.

CIKM-2015-WilkieA #performance #query

Query Length, Retrievability Bias and Performance (CW, LA), pp. 1787–1790.

ECIR-2015-WilkieA #comparison #difference #metric #retrieval

Retrievability and Retrieval Bias: A Comparison of Inequality Measures (CW, LA), pp. 209–214.

RecSys-2015-GuoD #approach #category theory

Uncovering Systematic Bias in Ratings across Categories: a Bayesian Approach (FG, DBD), pp. 317–320.

SIGIR-2015-LipaniLH #anti #precise

Splitting Water: Precision and Anti-Precision to Reduce Pool Bias (AL, ML, AH), pp. 103–112.

DiGRA-2014-MarteySSKCFSS #game studies #power of #testing

Testing the Power of Game Lessons: The Effects of Art and Narrative on Reducing Cognitive Biases (RMM, AS, JSG, KK, BAC, JEF, ETS, TS).

CHI-2014-Solomon

Customization bias in decision support systems (JS), pp. 3065–3074.

CIKM-2014-WilkieA #analysis #performance #retrieval

A Retrievability Analysis: Exploring the Relationship Between Retrieval Bias and Retrieval Performance (CW, LA), pp. 81–90.

ECIR-2014-HofmannSBR #evaluation #recommendation

Effects of Position Bias on Click-Based Recommender Evaluation (KH, AS, AB, MdR), pp. 624–630.

ECIR-2014-WilkieA #analysis #empirical #retrieval

Best and Fairest: An Empirical Analysis of Retrieval System Bias (CW, LA), pp. 13–25.

ECIR-2014-WilkieA14a

Efficiently Estimating Retrievability Bias (CW, LA), pp. 720–726.

ICML-c1-2014-Thomas #algorithm

Bias in Natural Actor-Critic Algorithms (PT), pp. 441–448.

ICPR-2014-CabreraMS

Systematic Labeling Bias: De-biasing Where Everyone is Wrong (GFC, CJM, JS), pp. 4417–4422.

KR-2014-PereiraDH #abduction #approach #reasoning

An Abductive Reasoning Approach to the Belief Bias Effect (LMP, EAD, SH).

RecSys-2014-AdamopoulosT14a #collaboration #on the #probability #recommendation

On over-specialization and concentration bias of recommendations: probabilistic neighborhood selection in collaborative filtering systems (PA, AT), pp. 153–160.

RecSys-2014-KrishnanPFG #learning #recommendation #social

A methodology for learning, analyzing, and mitigating social influence bias in recommender systems (SK, JP, MJF, KG), pp. 137–144.

SIGIR-2014-YeniterziC #testing

Analyzing bias in CQA-based expert finding test sets (RY, JC), pp. 967–970.

ASE-2014-KochharTL #debugging #locality #matter #question

Potential biases in bug localization: do they matter? (PSK, YT, DL), pp. 803–814.

DATE-2014-KhanAHKKRC #analysis

Bias Temperature Instability analysis of FinFET based SRAM cells (SK, IA, SH, HK, BK, PR, FC), pp. 1–6.

STOC-2014-BermanHT #constant

Coin flipping of any constant bias implies one-way functions (IB, IH, AT), pp. 398–407.

DHM-SET-2013-BiegBC #behaviour

Attentional Biases during Steering Behavior (HJB, HHB, LLC), pp. 21–27.

SEKE-2013-CalikliB #developer #fault #predict

The Impact of Confirmation Bias on the Release-based Defect Prediction of Developer Groups (GÇ, AB), pp. 461–466.

SIGIR-2013-AktolgaA #sentiment

Sentiment diversification with different biases (EA, JA), pp. 593–602.

SIGIR-2013-White #web

Beliefs and biases in web search (RW), pp. 3–12.

ESEC-FSE-2013-RahmanPHD #fault #predict

Sample size vs. bias in defect prediction (FR, DP, IH, PTD), pp. 147–157.

CHI-2012-AntinS #case study #motivation #self #social

Social desirability bias and self-reports of motivation: a study of amazon mechanical turk in the US and India (JA, ADS), pp. 2925–2934.

CHI-2012-DellVMCT #exclamation #human-computer #quote

“Yours is better!”: participant response bias in HCI (ND, VV, IM, EC, WT), pp. 1321–1330.

CIKM-2012-HofmannBR #on the

On caption bias in interleaving experiments (KH, FB, FR), pp. 115–124.

ICPR-2012-WangWZJ #analysis #database

Bias analyses of spontaneous facial expression database (ZW, SW, YZ, QJ), pp. 2926–2929.

SEKE-2012-Zhang #learning #named

i2Learning: Perpetual Learning through Bias Shifting (DZ), pp. 249–255.

ICSE-2012-GoreR #debugging #metric #statistics

Reducing confounding bias in predicate-level statistical debugging metrics (RG, PFRJ), pp. 463–473.

HCI-UA-2011-ItoIN #information management #parametricity #using

Method for Cultivating the “Inquiry-Mindset” Using the Information Access-Based Belief Bias Parameter (KI, YI, SN), pp. 48–57.

CIKM-2011-XingZZ #feedback #on the #problem

On bias problem in relevance feedback (QX, YZ, LZ), pp. 1965–1968.

KDD-2011-GuerraVMA #analysis #approach #realtime #sentiment

From bias to opinion: a transfer-learning approach to real-time sentiment analysis (PHCG, AV, WMJ, VA), pp. 150–158.

KDD-2011-MaiyaB #network #towards

Benefits of bias: towards better characterization of network sampling (ASM, TYBW), pp. 105–113.

WCRE-2010-NguyenAH #case study #dataset #debugging

A Case Study of Bias in Bug-Fix Datasets (THDN, BA, AEH), pp. 259–268.

CHI-2010-YangX #2d #towards

Bias towards regular configuration in 2D pointing (HY, XX), pp. 1391–1400.

CIKM-2010-PalK #community #identification

Expert identification in community question answering: exploring question selection bias (AP, JAK), pp. 1505–1508.

ICSE-2010-CalikliBA #analysis #developer #education #experience

An analysis of the effects of company culture, education and experience on confirmation bias levels of software developers and testers (GÇ, ABB, BA), pp. 187–190.

SAC-2010-LevyLMS #identification #multi

Identification and control of intrinsic bias in a multiscale computational model of drug addiction (YZL, DL, JSM, HTS), pp. 2389–2393.

DATE-2010-LongM #monitoring #network #optimisation

Optimization of the bias current network for accurate on-chip thermal monitoring (JL, SOM), pp. 1365–1368.

LATA-2009-MatobaNT #performance #symmetry

Efficiency of the Symmetry Bias in Grammar Acquisition (RM, MN, ST), pp. 566–577.

CHI-2009-ParkKCS #aspect-oriented #delivery #multi #named

NewsCube: delivering multiple aspects of news to mitigate media bias (SP, SK, SC, JS), pp. 443–452.

SIGIR-2009-WebberP

Score adjustment for correction of pooling bias (WW, LAFP), pp. 444–451.

ESEC-FSE-2009-BirdBADBFD #dataset #debugging

Fair and balanced?: bias in bug-fix datasets (CB, AB, EA, JD, AB, VF, PTD), pp. 121–130.

DATE-2009-PaciBB #adaptation #communication #effectiveness #variability

Effectiveness of adaptive supply voltage and body bias as post-silicon variability compensation techniques for full-swing and low-swing on-chip communication channels (GP, DB, LB), pp. 1404–1409.

CHI-2008-HartmannAS #experience #quality #user interface

Framing the user experience: information biases on website quality judgement (JH, ADA, AGS), pp. 855–864.

CIKM-2008-Sakai #metric #robust

Comparing metrics across TREC and NTCIR: the robustness to system bias (TS), pp. 581–590.

SIGIR-2008-Sakai #metric #robust

Comparing metrics across TREC and NTCIR: : the robustness to pool depth bias (TS), pp. 691–692.

DATE-2008-BacinschiMKG #adaptation

An Analog On-Chip Adaptive Body Bias Calibration for Reducing Mismatches in Transistor Pairs (PBB, TM, KK, MG), pp. 698–703.

DATE-2008-HongYBCEK #runtime #scalability

Dynamic Voltage Scaling of Supply and Body Bias Exploiting Software Runtime Distribution (SH, SY, BB, KMC, SKE, TK), pp. 242–247.

ICLP-2008-MuggletonST #declarative #logic programming #named #using

TopLog: ILP Using a Logic Program Declarative Bias (SM, JCAS, ATN), pp. 687–692.

ICLP-2008-Santos #declarative #logic programming #named #using

TopLog: ILP Using a Logic Program Declarative Bias (JCAS), pp. 818–819.

CHI-2007-AvrahamiFH #estimation

Biases in human estimation of interruptibility: effects and implications for practice (DA, JF, SEH), pp. 50–60.

KDD-2007-SmithE #classification #generative #robust

Making generative classifiers robust to selection bias (ATS, CE), pp. 657–666.

SIGIR-2007-CormackL07a #set

Power and bias of subset pooling strategies (GVC, TRL), pp. 837–838.

ICML-2006-SinghiL #classification #learning #set

Feature subset selection bias for classification learning (SKS, HL), pp. 849–856.

ICPR-v2-2006-HeLL #robust #segmentation

Robust Partial Volume Segmentation with Bias Field Correction in Brain MRI (HH, BL, KL), pp. 175–178.

KDD-2006-FanD #classification #framework #performance #testing

Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.

KDD-2006-LauwLW #statistics

Bias and controversy: beyond the statistical deviation (HWL, EPL, KW), pp. 625–630.

SIGIR-2006-BuckleyDSV

Bias and the limits of pooling (CB, DD, IS, EMV), pp. 619–620.

SAC-2006-ZamolotskikhDC #classification

A methodology for comparing classifiers that allow the control of bias (AZ, SJD, PC), pp. 582–587.

STOC-2005-AchlioptasCKM #graph #on the

On the bias of traceroute sampling: or, power-law degree distributions in regular graphs (DA, AC, DK, CM), pp. 694–703.

ICML-2004-MannorSST #estimation

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

ICML-2004-Zadrozny #classification #learning

Learning and evaluating classifiers under sample selection bias (BZ).

ICPR-v2-2004-NockP #estimation

Grouping with Bias for Distribution-Free Mixture Model Estimation (RN, VP), pp. 44–47.

DATE-v1-2004-ChenG #adaptation #low cost #performance #power management #reduction

A Low Cost Individual-Well Adaptive Body Bias (IWABB) Scheme for Leakage Power Reduction and Performance Enhancement in the Presence of Intra-Die Variations (TWC, JG), pp. 240–245.

ICML-2003-JensenNH #relational

Avoiding Bias when Aggregating Relational Data with Degree Disparity (DJ, JN, MH), pp. 274–281.

ICML-2003-ValentiniD

Low Bias Bagged Support Vector Machines (GV, TGD), pp. 752–759.

CIKM-2002-LiuYC #classification #induction

Boosting to correct inductive bias in text classification (YL, YY, JGC), pp. 348–355.

ICML-2002-JensenN #feature model #learning #relational

Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning (DJ, JN), pp. 259–266.

ICML-2001-DobraG #classification

Bias Correction in Classification Tree Construction (AD, JG), pp. 90–97.

DATE-2001-YildizSV #float #integer #linear #programming

Minimizing the number of floating bias voltage sources with integer linear programming (EY, AvS, CJMV), p. 816.

ICML-2000-VilaltaO #classification #distance #evaluation #metric #quantifier

A Quantification of Distance Bias Between Evaluation Metrics In Classification (RV, DO), pp. 1087–1094.

ICPR-v2-2000-HansenH #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.

ICPR-v2-2000-Schulerud #analysis #fault #feature model #linear

Bias of Error Rates in Linear Discriminant Analysis Caused by Feature Selection and Sample Size (HS), pp. 2372–2377.

ICPR-v3-2000-MateiM #reduction

Reduction of Bias in Maximum Likelihood Ellipse Fitting (BM, PM), pp. 3802–3806.

ICPR-v3-2000-ToczyskiP #estimation #geometry #linear #process

Complementary Linear Biases in Spatial Derivative Estimation for Improving Geometry-Driven Diffusion Processes (WDT, NP), pp. 3001–3006.

KDD-2000-FeldmanLRSS #approximate #framework #information management #specification

A framework for specifying explicit bias for revision of approximate information extraction rules (RF, YL, BR, YS, JS), pp. 189–197.

HCI-EI-1999-Suthers #collaboration

The Effects of Representational Bias on Collaborative Inquiry (DDS), pp. 362–366.

KDD-1998-FeeldersCM #mining

Mining in the Presence of Selectivity Bias and its Application to Reject Inference (AJF, SC, GJM), pp. 199–203.

HCI-SEC-1997-LowryHK #evolution #heuristic #human-computer #interface #robust

Heuristics and Biases in the Evolution of a Robust Human-Machine Interface Methodology (JCL, PEVH, SZK), pp. 323–326.

ICML-1997-TodorovskiD #declarative #equation

Declarative Bias in Equation Discovery (LT, SD), pp. 376–384.

CAiSE-1996-SiauWB #modelling

When Parents Need Not Have Children — Cognitive Biases in Information Modeling (KS, YW, IB), pp. 402–420.

ICML-1996-KahaviW #composition

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

ICML-1996-Sebag #approach

Delaying the Choice of Bias: A Disjunctive Version Space Approach (MS), pp. 444–452.

ICML-1995-BrunkP #semantics

A Lexical Based Semantic Bias for Theory Revision (CB, MJP), pp. 81–89.

ICML-1995-KongD

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

ICML-1994-Pereira #machine learning #natural language #problem

Frequencies vs. Biases: Machine Learning Problems in Natural Language Processing — Abstract (FCNP), p. 380.

KDD-1994-ZuckerCTR #induction #named

DICE: A Discovery Environment Integrating Inductive Bias (JDZ, VC, JT, GR), pp. 275–286.

ICDAR-1993-TakeshitaNK #distance #on the

On the bias of Mahalanobis distance due to limited sample size effect (TT, SN, FK), pp. 171–174.

ICML-1993-Caruana #induction #knowledge-based #learning #multi

Multitask Learning: A Knowledge-Based Source of Inductive Bias (RC), pp. 41–48.

ICML-1993-Tadepalli #learning #query

Learning from Queries and Examples with Tree-structured Bias (PT), pp. 322–329.

ML-1991-desJardins #learning #probability

Probabilistic Evaluating of Bias for Learning Systems (Md), pp. 495–499.

ML-1991-MartinB #learning #variability

Variability Bias and Category Learning (JDM, DB), pp. 90–94.

ML-1989-CaruanaSE #algorithm #induction #multi #search-based #using

Using Multiple Representations to Improve Inductive Bias: Gray and Binary Coding for Genetic Algorithms (RC, JDS, LJE), pp. 375–378.

ML-1989-Chrisman

Evaluating Bias During Pac-Learning (LC), pp. 469–471.

ML-1989-Danyluk #induction #information management

Finding New Rules for Incomplete Theories: Explicit Biases for Induction with Contextual Information (APD), pp. 34–36.

ML-1989-Gordon

Screening Hypotheses with Explicit Bias (DFG), pp. 499–500.

ML-1989-GrosofR #declarative

Declarative Bias for Structural Domains (BNG, SJR), pp. 480–482.

ML-1989-Marie #dependence #learning

Building A Learning Bias from Perceived Dependencies (CdSM), pp. 501–502.

ML-1989-Tallis

Overcoming Feature Space Bias in a Reactive Environment (HT), pp. 505–508.

ML-1988-CaruanaS #algorithm #representation #search-based

Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms (RC, JDS), pp. 153–161.