ABOUT ML aims to improve transparency in ML lifecycle documentation.
problem Lack of standard documentation in machine learning lifecycle.
method Initiative to operationalize ML transparency and standardize documentation.
result Helps address gaps in ML lifecycle documentation.
This paper introduces C-DSL to improve data mining outcomes by considering context.
problem Data collection ambiguities, data imbalance, hidden biases, lack of domain info, and data incompleteness.
method Developed Context-Driven Data Science Lifecycle (C-DSL) to address data quality issues.
result Tangible improvements to data mining outcomes were achieved through C-DSL.
Survey of methods for ML assurance across its lifecycle stages.
problem Ensuring safety of ML in safety-critical applications.
method Comprehensive survey of methods at each ML lifecycle stage.
result Identification of open challenges in ML assurance.
The paper optimizes DIA purchase policies using lifecycle models and asset allocation.
problem Determining the optimal allocation to Deferred Income Annuities (DIAs).
method Employed a lifecycle model with utility of consumption and bequest, formalized optimization process, analyzed results, and extended model to include asset allocation.
result Optimal DIA allocation varies based on refundability, asset allocation, and perceived longevity.
A framework combining HSMM and survival analysis for lifecycle-oriented mobility analysis.
problem Understanding individual metro usage dynamics over multi-year horizons.
method A state-based lifecycle modeling framework integrating HSMM and discrete-time survival analysis.
result Identification of interpretable mobility states, transition dynamics, and state-dependent exit and re-entry processes.
A dynamic model of the product lifecycle of (nearly) homogeneous durables in polypoly markets is established. It describes the concurrent evolution of the unit sales and price of durable goods. The theory is based on the idea that the sales dynamics is determined by a meeting process of demanded with supplied product u…
A new microeconomic model is presented that aims at a description of the long-term unit sales and price evolution of homogeneous non-durable goods in polypoly markets. It merges the product lifecycle approach with the price dispersion dynamics of homogeneous goods. The model predicts a minimum critical lifetime of non-…
Improving software quality through effective organizational learning.
problem Lack of reliable quantification methods for software evolution.
method Leveraging application lifecycle management data to identify and address managerial practices.
result Effective learning from past processes improves software quality indirectly.
Homeownership boosts wealth and welfare compared to renting, according to new research.
problem The conventional wisdom that renting is better than owning a home.
method Block-bootstrap lifecycle simulation to compare homeownership and renting strategies.
result Homeownership generates more wealth and welfare gains than renting, especially for households with high labor income.
Industry lacks tools to secure ML systems, study finds.
problem Insufficient security tools for ML systems in industry.
method Interviews with 28 organizations to identify gaps.
result Need revised Security Development Lifecycle for ML.
RED-2400 is a public benchmark of trading events from a Solana exchange, labeled by algorithmic rejection.
problem Analyzing algorithmically-rejected trading events for insights into market dynamics.
method Public dataset of 6,660 algorithmically-rejected trading events, linked to post-rejection price and liquidity trajectories.
result First window of a planned series of datasets extending the time horizon and enabling regime-stratified analysis.
Optimizes impression allocation for e-commerce platforms using reinforcement learning.
problem Short-term and long-term returns are not optimized in current e-commerce platform allocation mechanisms.
method Formal lifecycle model of products, reinforcement learning framework, first principal component based permutation, novel experiences generation method.
result Significant improvement in platform and participant health with optimized impression allocation.
We extend the lifecycle model (LCM) of consumption over a random horizon (a.k.a. the Yaari model) to a world in which (i.) the force of mortality obeys a diffusion process as opposed to being deterministic, and (ii.) a consumer can adapt their consumption strategy to new information about their mortality rate (a.k.a. h…
Focuses on monitoring and explaining models in real-world applications.
problem Ensuring high quality machine learning services in production environments.
method Statistical techniques for model performance and data monitoring, explanations of predictions.
result Challenges and solutions for implementing monitoring and explanation in production models.
A new indicator measures project risk from activity durations.
problem Managing project risks throughout the lifecycle.
method Activity Risk Index (ARI) based on Schedule Risk Baseline.
result Identifies activities contributing most to project uncertainty.
The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. The opportunities for using data mining techniques in the "digital oil-field" remain largely unexplored or uncharted. With the high rate of data expansion, companies are scrambling to develo…
The paper audits trading filters, finding a high save-to-miss ratio.
problem Improving the efficiency and accuracy of trading filters in decentralized exchanges.
method A precision audit of filter rules against real trading data, classifying rejection events.
result Conservative save-to-miss ratio of 3.7 : 1, with wider interpretation of 14.8 : 1.
Deep learning models can discriminate against certain groups, requiring computational methods to ensure fairness.
problem Algorithmic discrimination in deep learning models affecting protected groups.
method Interpretability and mitigation approaches at different stages of deep learning lifecycle.
result Interpretability aids in diagnosing and mitigating algorithmic discrimination in deep learning.
This paper advances theory on the process of collaboration between entities and its implications on the quality of services, information, and/or products (SIPs) that the collaborating entities provide to each other. It investigates the scenario of outsourced IS projects (such as custom software development) where the e…
SaML guides ML models to avoid survey biases.
problem ML models trained on survey data often ignore survey design metadata.
method Nine-step guideline for incorporating survey design metadata in ML lifecycle.
result SaML provides valid population inference from survey data.
Three methods detect informed trading on prediction markets, each focusing on different aspects.
problem Detecting informed trading in decentralized prediction markets.
method Composite screen, event-level sign-randomization test, and Information Leakage Score (ILS) framework.
result Different methods detect informed trading on prediction markets, each focusing on different aspects.
STAD adapts models to evolving time-based data shifts.
problem Gradual distribution shifts over time challenge existing test-time adaptation methods.
method Bayesian filtering method that learns time-varying dynamics in hidden features.
result STAD excels in handling small batch sizes and label shift on real-world data.
PredictionMarketBench benchmarks trading agents on prediction markets.
problem Evaluating trading agents on prediction markets with realistic conditions.
method Deterministic replay of historical data, execution-realistic simulator, agent interface.
result Fee-aware algorithmic strategies outperform naive agents in volatile episodes.
This study examines non-retail trading on Polymarket, revealing unique behavior patterns and structural limitations.
problem Lack of address-level quote-lifecycle data in Polymarket prediction markets.
method Empirical analysis of 13 million order-filled events using DBSCAN clustering on a six-feature fill-side vector.
result Non-retail behavior is uni-modal, contradicting previous archetypal hypotheses.
New attacks improve privacy audits by analyzing model updates.
problem Improving privacy audits of AI models through sequence analysis.
method Developed SeMI attacks to identify target insertions in model sequences.
result SeMI attacks achieve higher power and tighter privacy audits.
Framework for monitoring ML model performance in production without labels.
problem Monitoring real-time prediction quality of ML models in production without labels.
method ML Health framework using diagnostic methods to generate alerts for further investigation.
result The method outperforms standard distance metrics at detecting issues with mismatched data sets.
In life-cycle economics the Samuelson paradigm (Samuelson, 1969) states that the optimal investment is in constant proportions out of lifetime wealth composed of current savings and the present value of future income. It is well known that in the presence of credit constraints this paradigm no longer applies. Instead, …
Systematic review of ML models for detecting social media deception.
problem Detecting fake news, spam, and fake accounts on social media.
method 36 studies evaluated using PROBAST tool, identifying biases and limitations.
result Over-reliance on accuracy in imbalanced data settings is a flaw.
ML .NET simplifies integrating machine learning into software development.
problem Difficulty and cost of incorporating machine learning in software development.
method Developed a framework (ML .NET) and introduced DataView for efficient data abstraction.
result ML .NET outperforms recent machine learning frameworks in performance studies.
This work introduces a bias-variance decomposition for proper scores, improving uncertainty estimation in predictive models.
problem Reliable uncertainty estimation for predictions in safety-critical applications, especially under domain drift.
method Developed a general bias-variance decomposition for proper scores, introducing the Bregman Information as the variance term.
result The decomposition provides novel formulations for different predictive tasks, including classification and model ensembles.
Geometric stability predicts steerability and detects drift in language models.
problem Predicting steerability and detecting drift in language models.
method Supervised and unsupervised geometric stability measures.
result Supervised geometric stability predicts steerability with high accuracy and detects drift earlier.
Foundation models alter medical data science workflow, challenging veridical data science principles.
problem Foundation models disrupt traditional data science practices in medicine.
method Critically examined the medical foundation model lifecycle and its deviation from veridical data science principles.
result Foundation models challenge veridical data science principles of predictability, computability, and stability.
The paper tackles model failure detection and refitting in real-world systems.
problem Real-world data often fails statistical models due to heterogeneity.
method Develops tools for detecting and identifying model failures and refitting to improve accuracy.
result Empirical and theoretical results show the effectiveness of the proposed methodology.
The paper models retirement spending using biological age instead of chronological age.
problem Retirement spending varies at the same chronological age.
method Developed a stochastic mortality model to adjust for biological age.
result Optimal consumption rates derived using biological age.
The paper proposes a method to identify fair features in ML data integration.
problem Ensuring fairness in machine learning data integration.
method Causal interventional fairness, conditional independence tests, group testing.
result The proposed algorithm identifies fair features without biasing the dataset.
The Australian Government uses the means-test as a way of managing the pension budget. Changes in Age Pension policy impose difficulties in retirement modelling due to policy risk, but any major changes tend to be `grandfathered' meaning that current retirees are exempt from the new changes. In 2015, two important chan…
Blockchain helps secure payments between AI agents.
problem Ensuring secure payments between untrusted AI agents.
method Systematized four-stage lifecycle for A2A payments on blockchain.
result Challenges remain in weak intent binding, misuse, and limited accountability.
Study finds consumers are more price-sensitive before livestreams than after.
problem Understanding consumer demand during livestreaming lifecycle.
method Examined consumer demand for live events and recorded versions using data from a livestreaming platform.
result Demand is more price-sensitive before livestreams than after.
System detects overfitting in ML apps, improving quality and efficiency.
problem Overfitting in ML applications during continuous development.
method ease. ml/meter system for automated overfitting detection and measurement.
result Probabilistic overfitting signals for developers to take actions.
Study identifies NFT whales driving the market with consistent high returns.
problem Lack of financial analysis of NFT trading ecosystem.
method Longitudinal study of 3.8M NFT transactions, classifying traders into whales, dolphins, and minnows.
result Top 0.1% of NFT traders (whales) drive the market with consistent, high returns.
Isthmus platform simplifies ML/AI integration in healthcare.
problem Challenges in deploying ML models in healthcare due to data quality, regulatory, and security issues.
method Turnkey, cloud-based platform addressing data quality, clinical relevance, and regulatory compliance.
result Reduces time to market for operationalizing ML/AI in healthcare.
Large language models struggle with causal relationships, leading to biases and hallucinations.
problem LLMs struggle with true causal relationships, leading to biases and hallucinations.
method Embed causality into LLMs training process at every stage.
result LLMs need to be trained to understand and apply causal knowledge, not just recite it.
FairPrep aims to improve fairness in machine learning by providing best practices.
problem Lack of best practices in fairness-enhancing interventions.
method Developer-centered design and evaluation framework for fairness-enhancing interventions.
result Hyperparameter tuning and data cleaning methods impact fairness outcomes.
This study categorizes RWA tokenization challenges and solutions.
problem Navigating the gap between on-chain deterministic code and off-chain probabilistic reality.
method Taxonomy and comparative analysis of RWA protocols, legal and technical standards.
result RWA tokenization requires overcoming legal and technical interoperability issues.
Unified framework explains retirement and annuitization decisions under age-dependent mortality.
problem Complexity of annuitization decisions due to longevity risk and labor force participation.
method Stochastic control and optimal stopping framework with habit formation and endogenous labor supply.
result Rich sequence of retirement dynamics, including defensive and aggressive labor supply phases.
ReSkill reconciles RL skill creation with policy optimization.
problem RL policies lack reusable strategies across tasks.
method Integrates skill creation into RL loop with three mechanisms.
result Consistently outperforms existing methods, especially on unseen tasks.
Stablecoins offer efficient settlement but externalize costs and risks.
problem Comparing stablecoins to card networks in retail payments.
method Unified analytical framework (CLEAR) across five dimensions.
result Stablecoins are advantageous in closed-loop and high-friction contexts but structurally disadvantaged as open-loop instruments.
Polymarket-v1 Database tracks 1.2B trades across 1.3M markets with 100% ground-truth direction.
problem Lack of ground-truth data in prediction markets archives.
method Ground-truth archive of 1.2B trades from Polymarket's CTF Exchange.
result Ground-truth data reveals systematic errors in microstructure metrics.