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Jointly Minimizing the Expected Costs of Review for Responsiveness and Privilege in E-Discovery
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1017/cbo9780511609220.014openalex-snapshot
Prospect theory: An analysis of decision under risk
inferredcites →https://doi.org/10.1023/a:1007413511361openalex-snapshot
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
inferredcites →https://doi.org/10.1109/bigdata.2015.7363867openalex-snapshot
Batch-mode active learning for technology-assisted review
inferredcites →https://doi.org/10.1109/icdm.2015.137openalex-snapshot
Accurate Estimation of Generalization Performance for Active Learning
inferredcites →https://doi.org/10.1145/1148170.1148216openalex-snapshot
Tackling concept drift by temporal inductive transfer
inferredcites →https://doi.org/10.1145/1390156openalex-snapshot
Proceedings of the 25th international conference on Machine learning - ICML '08
inferredcites →https://doi.org/10.1145/2505515.2505708openalex-snapshot
Towards minimizing the annotation cost of certified text classification
inferredcites →https://doi.org/10.1145/2600428.2609506openalex-snapshot
Assessing the reliability and reusability of an E-discovery privilege test collection
inferredcites →https://doi.org/10.1145/2600428.2609601openalex-snapshot
Evaluation of machine-learning protocols for technology-assisted review in electronic discovery
inferredcites →https://doi.org/10.1145/2742548openalex-snapshot
Utility-Theoretic Ranking for Semiautomated Text Classification
inferredcites →https://doi.org/10.1145/2746090.2746101openalex-snapshot
Evaluating expertise and sample bias effects for privilege classification in e-discovery
inferredcites →https://doi.org/10.1145/2766462.2767771openalex-snapshot
Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review
inferredcites →https://doi.org/10.1145/2806416.2806597openalex-snapshot
Semi-Automated Text Classification for Sensitivity Identification
inferredcites →https://doi.org/10.1145/2854946.2854964openalex-snapshot
An AID for Avoiding Inadvertent Disclosure
inferredcites →https://doi.org/10.1145/775047.775151openalex-snapshot
Transforming classifier scores into accurate multiclass probability estimates
inferredcites →https://doi.org/10.1561/1500000025openalex-snapshot
Information Retrieval for E-Discovery
inferredcites →https://doi.org/10.17877/de290r-14262openalex-snapshot
Making Large-Scale SVM Learning Practical
inferredcites →https://doi.org/10.17877/de290r-5102openalex-snapshot
Estimating the generalization performance of a SVM efficiently
inferredcites →https://doi.org/10.2307/1914185openalex-snapshot
Prospect Theory: An Analysis of Decision under Risk
inferredcites →https://doi.org/10.2307/2185642openalex-snapshot
Foundations of Rational Choice Under Risk.
inferredcites →https://doi.org/10.2307/2987588openalex-snapshot
The Comparison and Evaluation of Forecasters
inferredcites →https://doi.org/10.48550/arxiv.1504.06868openalex-snapshot
Autonomy and Reliability of Continuous Active Learning for Technology-Assisted Review
inferredcites →https://doi.org/10.5555/1005332.1005345openalex-snapshot
RCV1: A New Benchmark Collection for Text Categorization Research
inferredcites →https://doi.org/10.5555/188490.188495openalex-snapshot
A sequential algorithm for training text classifiers
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
inferredcites →https://doi.org/10.7551/mitpress/6173.003.0010openalex-snapshot
Transductive Support Vector Machines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-99736-6_34openalex-snapshot
Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review
inferred← citeshttps://doi.org/10.1007/978-3-031-10706-1_6openalex-snapshot
The Digital Forensic Approach to eDiscovery
inferred← citeshttps://doi.org/10.1007/978-3-031-20467-8_1openalex-snapshot
The Case for Quantification
inferred← citeshttps://doi.org/10.1007/978-3-031-20467-8_2openalex-snapshot
Applications of Quantification
inferred← citeshttps://doi.org/10.1007/978-3-031-20467-8_3openalex-snapshot
Evaluation of Quantification Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-031-20467-8_4openalex-snapshot
Methods for Learning to Quantify
inferred← citeshttps://doi.org/10.1007/978-3-031-20467-8_6openalex-snapshot
The Quantification Landscape
inferred← citeshttps://doi.org/10.1007/s10618-023-00961-5openalex-snapshot
SALτ: efficiently stopping TAR by improving priors estimates
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103069openalex-snapshot
Legal case document similarity: You need both network and text
inferred← citeshttps://doi.org/10.1016/j.iswa.2023.200209openalex-snapshot
Improved risk minimization algorithms for technology-assisted review
inferred← citeshttps://doi.org/10.1109/bigdata52589.2021.9672008openalex-snapshot
An Empirical Study on Transfer Learning for Privilege Review
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10826118openalex-snapshot
A Hybrid Approach for Privilege Document Review: Rule-Based and Machine Learning
inferred← citeshttps://doi.org/10.1145/3388640openalex-snapshot
Towards Question-based High-recall Information Retrieval
inferred← citeshttps://doi.org/10.1145/3411755openalex-snapshot
When to Stop Reviewing in Technology-Assisted Reviews
inferred← citeshttps://doi.org/10.1145/3433164openalex-snapshot
A Critical Reassessment of the Saerens-Latinne-Decaestecker Algorithm for Posterior Probability Adjustment
inferred← citeshttps://doi.org/10.1145/3453146openalex-snapshot
Lost in Transduction: Transductive Transfer Learning in Text Classification
inferred← citeshttps://doi.org/10.1145/3469096.3469872openalex-snapshot
On minimizing cost in legal document review workflows
inferred← citeshttps://doi.org/10.1145/3481045openalex-snapshot
Providing More Efficient Access to Government Records: A Use Case Involving Application of Machine Learning to Improve FOIA Review for the Deliberative Process Privilege
inferred← citeshttps://doi.org/10.1145/3631990openalex-snapshot
Stopping Methods for Technology-assisted Reviews Based on Point Processes
inferred← citeshttps://doi.org/10.1145/3726302.3729916openalex-snapshot
LLM-Assisted Relevance Assessments: When Should We Ask LLMs for Help?
inferred← citeshttps://doi.org/10.18653/v1/2023.findings-emnlp.171openalex-snapshot
Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review
inferred← citeshttps://doi.org/10.48550/arxiv.2108.07258openalex-snapshot
On the Opportunities and Risks of Foundation Models
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