Target Risk

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2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Latest papers 17

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Scalable Cox Regression via Grouped Risk Sets and Sharper LogSumExp Rates
Sep 30, 2026Elizaveta Iashchinskaia, Egor GladinTime-To-Event Data Logistic Regression
HSE University
Revisiting Risky Tackle Detection with Vision Transformers
Sep 28, 2026Syed Ahsan Masud Zaidi, Lior Shamir, Scott DietrichSelf-Supervised Vision Transformers Vision Transformer
Kansas State University, Manhattan, KS, USA · Albright College, Reading, PA, USA
NeuronSifter: Intervention Planning in CNS Microenvironments
Sep 28, 2026Haowei Xu, Wanyi Fu, Hongbin Han +1Controlled Study Decisions
Institute of Medical Technology, Peking University Health Science Center, Beijing, China · Beijing Key Laboratory of Intelligent Neuromodulation and Brain Disorder Treatment, Beijing, China · Department of Radiology, Peking University Third Hospital, Beijing, China +1
Beyond Retrieval Relevance: Scene-Grounded Risk Entailment for Vision-Language Driving
Sep 28, 2026Jiaxin Liu, Ruilin Yu, Liang Peng +8Scene Reasoning Hazard
School of Vehicle and Mobility, Tsinghua University · Xiaomi EV · Jilin University
From Position Risks to Block Survival: Faster Generation for Diffusion Language Models
Sep 27, 2026Siwei Chen, Yuxiang Wan, Yifan Yu +1Diffusion Language Models Diffusion Models
University of Illinois Urbana-Champaign
DefaultGNN: A Dual-Perspective GNN Framework for Predicting Corporate Default from Buyer-Seller Transaction Networks
Sep 22, 2026Junghoon Kim, Hyunsung Kim, Seungyoon Choi +4Credit Risk Prediction Gnn-Based Detectors
KAIST Daejeon, Republic of Korea · Techfin Ratings Seoul, Republic of Korea · Douzone Seoul, Republic of Korea
MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows
Aug 11, 2026Yiqi Wang, Zihao Yan, Jiaqi Zhang +5Graph-Structured Memories Multi-Agent Workflows
Long-Term Sequential Decision Making under Risk
Jul 22, 2026Irmaan, Mirzanejad, Nadjet Bourdache +1Target Risk Sequential Decision Making
Mohammad · Université de Caen Normandie, ENSICAEN, CNRS, Normandie Univ, GREYC UMR 6072, France
Subjective Risk Decomposition: A New View for Uncertainty Quantification
Jul 16, 2026Raghad Alamri, Michele Caprio, Gavin BrownUncertainty Quantification Uncertainty
Department of Computer Science, The University of Manchester · Department of Computer Science, University of Warwick
Auditing the Risk Claims of Distributional Reinforcement Learning
Jul 13, 2026Hari PrasadDistributional Reinforcement Learning Target Risk
A Mechanism-Driven Theory of Phase Transitions in Active Learning
Jun 30, 2026Julia Machnio, Mads Nielsen, Mostafa Mehdipour GhaziActive Learning Learnability
Pioneer Centre for AI, University of Copenhagen, Copenhagen, Denmark
Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
Jun 12, 2026Annie Ulichney, Amanda CostonCovariate Shift Selection Bias
Department of Statistics, University of California, Berkeley
Decision-Making under Combinatorial Risk
Jun 8, 2026Yifan Hong, Hongmiao Fan, Chen WangTarget Risk Risk
Department of Industrial Engineering, Tsinghua University
CART Random Forests as Sequential Allocation over Random Opportunity Sets: A Stochastic-Control Theory of Ensemble Risk
May 26, 2026Tianxing Mei, Yingying Fan, Mingming Leng +1Random Forest Target Risk
Faculty of Business, Lingnan University · Data Sciences and Operations Department, University of Southern California
Algometrics: Forecasting Under Algorithmic Feedback
May 13, 2026Marc SchmittData-Driven Forecasting Target Risk
University of Oxford
Measurement Risk in Supervised Financial NLP: Rubric and Metric Sensitivity on JF-ICR
Apr 30, 2026Sidi Chang, Peiying Zhu, Yuxiao Chen +1Legal Natural Language Processing Benchmarks Task-Specific Rubrics
Blossom AI Labs, Tokyo, Japan · Blossom AI Labs, San Francisco, USA
Estimation of multiple mean vectors in high dimension
Mar 22, 2024Gilles Blanchard, Jean-Baptiste Fermanian, Hannah MarienwaldMean Target Risk
LMO, DATASHAPE · Université Paris Saclay, Institut Mathématique d’Orsay, France. · LMO +2

Sep 30, 2026, cs.LGJ/K move · Enter open · S save

Scalable Cox Regression via Grouped Risk Sets and Sharper LogSumExp Rates

Elizaveta Iashchinskaia, Egor Gladin

HSE University

Time-To-Event Data Logistic Regression Exponential Family Target Risk Batch Normalization

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Motivated by the computational challenges of large-scale Cox regression, we study stochastic minimization of LogSumExp objectives over large sets. Mini-batch normalizer estimates generally yield biased gradients. We instead use a softplus surrogate that introduces one auxiliary scalar per normalizer and admits unbiased single-sample gradients. For smooth convex LogSumExp objectives, we prove an

O(T^{-1/2})

averaged objective bound, improving the previous

T^{-1/4}

analysis. With a strongly convex regularizer on the original variable, we also obtain a last-iterate squared-error rate of

\widetilde{O}(T^{-1})

without strong convexity in the auxiliary variables. For Cox regression, the normalizers are defined over nested risk sets. We exploit this structure by grouping neighboring failures and sharing one auxiliary variable per group. The resulting compressed objective admits uniform score and curvature bounds that control the errors from grouping and softplus approximation. Together with the general optimization result, these bounds give a mean-square rate of

T^{-4/5}

, up to logarithmic factors, relative to the full Cox solution. The compressed estimator also matches the full estimator's asymptotic distribution. Experiments on synthetic and real survival datasets with slowly decreasing risk sets show a favorable performance relative to stochastic baselines.

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