Semiparametric Framework

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On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models
Sep 16, 2026Sambit Mishra, Urbashi MitraStructural Equation Models Identifiability
A Unified Causal Inference Framework for the Desirability of Outcome Ranking Paradigm in Benefit-Risk Evaluation
Aug 5, 2026Yuan Feng, Shiyu Shu, Yixin Fang +4Heterogeneous Treatment Effects Causal Inferences
Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue
Aug 4, 2026Xueping Gong, Zhuoluo Zhang, Zhaowei Miao +1Prices Semiparametric Framework
A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models
Jul 26, 2026Trung Phung, Ilya ShpitserSemiparametric Framework Tangent Space
Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks
Jul 24, 2026Masahiro TanakaStructural Equation Models Heteroskedasticity
An efficient adaptive dimension selection algorithm for multidimensional probit graded response models
Jul 20, 2026Yu Zhou, Yincai Tang, Bin Lv +1Semiparametric Framework Feature Selection
A Semiparametric Framework for Stochastic Fundamental Diagram Modeling
Jul 17, 2026Pengnan Chi, Xiaoliang Ma, Magnus Jansson +1Stochastic Systems Traffic
Diversified Multinomial Logit Contextual Bandits
Jul 13, 2026Heesang Ann, Taehyun Hwang, Min-hwan OhGeneralized Linear Bandit Bandits
Estimation, Prediction, and Assortment Optimization for Markov Chain Choice Models with Panel Data
Jul 10, 2026Yalcin Akcay, Gerardo Berbeglia, Young-San LinDiscrete Choice Models Semiparametric Framework
Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning
Jul 9, 2026Zijie Cheng, Yang Peng, Zhihua ZhangQuantile Regression Distributional Learning
Heckman-Corrected Epistemic Uncertainty: Selection on Unobservables Defeats Importance Weighting
Jul 7, 2026Gunner Levi HoweSelection Bias Covariate Shift
FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture
Jul 5, 2026Zijian Wang, Pengfei Li, Guangyu Yang +1Heterogeneous Federated Learning Federated Learning
A Novel Machine Learning Approach for Central Nervous System Tumor Classification from DNA Methylation
Jul 1, 2026Paulo R. Ferreira, Lucas Coutinho Freitas, Laís dos Santos Gonçalves +4Glioma Non-Small Cell Lung Cancer
From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research
Jul 1, 2026Ka Ching Chan, Qiana Liu, Sanjib Tiwari +1Structural Equation Models Semiparametric Framework
Gradient boosting with vector-valued leafs
Jun 28, 2026David CortesGradient Boosted Tree Decision Trees
Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC
Jun 25, 2026Krzysztof Pysz, Artur Bartczak, Jarosław Kwiecień +2Multiple Instance Learning Non-Small Cell Lung Cancer
Embedding Foundation Model Predictions in Discrete-Choice Models with Structural Guarantees
Jun 24, 2026Yingshuo Wang, Xian Sun, Yanhang Li +2Discrete Choice Models Semiparametric Framework
Decision-Focused Learning: When and Why Traditional Prediction Models Fail
Jun 19, 2026Mo LiuPredictive Uncertainty Sequential Decision Making
Orthogonal Discrepancy Kernels for Learning with Partial Physics
Jun 19, 2026Swapnil Manna, Timothy J. Rogers, Lawrence BullSystem Identification Discrepancy
Attention-Based Estimation of the Individual Treatment Benefit Probability under Dose Variation
Jun 11, 2026Lev V. Utkin, Andrei V. Konstantinov, Stanislav K. Kogan +2Treatment Effect Heterogeneous Treatment Effects
AI Receptivity or AI Adoption Breadth? A Tool-Specific Reanalysis of the Lower-Literacy/Higher-Usage Link
Jun 11, 2026Hristo InouzheArtificial Intelligence Literacy Artificial Intelligence Systems
Efficient Multinomial Logistic Bandit via Frequent Directions
Jun 10, 2026Linzhe He, Yu-Jie Zhang, Sifan Yang +1Generalized Linear Bandit Semiparametric Framework
Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides
Jun 9, 2026Rahul Roy, Nur Sunar, Jayashankar M. SwaminathanLinear Regret Semiparametric Framework
Deep Single-Index Fréchet Regression
Jun 5, 2026Muqing Cui, Yidong Zhou, Su I Iao +1High-Dimensional Data Fréchet Inception Distance
Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis
Jun 1, 2026Itai Zilberstein, Ioannis Anagnostides, Tuomas SandholmSurvival Predictions Survival Analysis
Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity
May 26, 2026Jakub Wornbard, Zikai Shen, Dimitri Meunier +1Heteroskedasticity Semiparametric Framework
Optimal Design for Multinomial Logit Model with Applications to Best Assortment Identification
May 25, 2026Joongkyu Lee, Min-hwan OhGeneralized Linear Bandit Bayesian Experimental Design
Valid and Expressive Copulas for Irregular Multivariate Time Series
May 22, 2026Christian Klötergens, Tom Hanika, Lars Schmidt-Thieme +1Gaussian Copula Multivariate Time Series Forecasting
Semiparametric Efficient Bilevel Gradient Estimation
May 20, 2026Fares El Khoury, Houssam Zenati, Nathan Kallus +2Bilevel Optimization Semiparametric Framework
Adaptive Experimentation for Censored Survival Outcomes
May 18, 2026Yuxin Wang, Dennis Frauen, Jonas Schweisthal +3Survival Analysis Treatment Effect
Learning in Position-Aware Multinomial Logit Bandits: From Multiplicative to General Position Effects
May 17, 2026Xi Chen, Shibo Dai, Jiameng Lyu +1Generalized Linear Bandit Semiparametric Framework
Sharp Spectral Thresholds for Logit Fixed Points
May 15, 2026Tongxi WangEntropy-Regularized Equilibrium Selection Gumbel-Softmax Relaxation
Harnessing Unimodality in Semiparametric Contextual Pricing via Oracle Price Map Learning
May 14, 2026Yingying Fan, Yuxuan Han, Jinchi Lv +2Prices Linear Contextual Bandits
Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation
May 11, 2026George PanagopoulosHeterogeneous Treatment Effects Semiparametric Framework
Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
May 8, 2026Houssam Zenati, Arthur GrettonHeterogeneous Treatment Effects Two-Sample Testing
Optimizing Social Utility in Sequential Experiments
May 7, 2026Ander Artola Velasco, Stratis Tsirtsis, Manuel Gomez-RodriguezExpected Utility Bayesian Experimental Design
OTSS: Output-Targeted Soft Segmentation for Contextual Decision-Weight Learning
Apr 30, 2026Renjun Hu, Hyun-Soo AhnSemiparametric Framework Gumbel-Softmax Relaxation
Logistic Bandits with $\tilde{O}(\sqrt{dT})$ Regret without Context Diversity AssumptionsLogistic Bandits with \tilde{O}(\sqrt{dT}) Regret without Context Diversity Assumptions
Apr 24, 2026Seoungbin Bae, Dabeen LeeO(T^Β)$ Simultaneous Regret Multi-Armed Bandits
Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics
Apr 20, 2026Khang Tran, Khoa Nguyen, Cristian Borcea +1Test Generation Program Analysis
LLM Evaluation as Tensor Completion: Low Rank Structure and Semiparametric Efficiency
Apr 7, 2026Jiachun Li, David Simchi-Levi, Will Wei SunLarge Language Model Evaluation Tensor Completion
Robust Weighted Triangulation of Causal Effects Under Model Uncertainty
Mar 1, 2026Rohit Bhattacharya, Ina Ocelli, Ted WestlingCausal Inferences Semiparametric Framework
Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits
Feb 2, 2026Seoungbin Bae, Junyoung Son, Dabeen LeeLarge Language Model Routing Linear Contextual Bandits
Semi-parametric Functional Classification via Path Signatures Logistic Regression with Adaptive Order Selection
Jul 9, 2025Pengcheng Zeng, Siyuan JiangSemiparametric Framework Logistic Regression
Semiparametric Inference for Counterfactual Regression under Intervention-Driven Shift
Apr 3, 2025Kwangho KimSemiparametric Framework Counterfactual Reasoning
Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models
Jan 28, 2023Shuting Shen, Xi Chen, Ethan X. Fang +1Semiparametric Framework Generalized Linear Bandit
Policy design in experiments with unknown interference
Nov 16, 2020Davide Viviano, Jess RudderBayesian Experimental Design Welfare
Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects
Date pendingAnish Agarwal, Sukjin Han, Dwaipayan Saha +2Synthetic Samples Treatment Effect

Sep 16, 2026 · cs.LGJ/K move · Enter open · S save

On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models

Sambit Mishra, Urbashi Mitra

The problem of identifiability in linear parametric models (LPMs) whose nodes follow either an ordered logit model or a regular one-parameter exponential family is evaluated. The results go beyond classical structural equation models as well as results for nodes with observations from a homogeneous family of distributions. The main result establishes that the orientation of every edge joining an ordinal node to an exponential-family node is identifiable from the joint distribution alone at every parameter value, provided the ordinal node has at least three categories and the exponential-family node at least three points of support, with no restriction on the sufficient statistic. Converses show that both requirements are necessary: the three-category requirement is binding only for affine sufficient statistics, and the three-point requirement is binding under the canonical link. The guarantee extends to orienting every such mixed ordinal-exponential family edge of a given

d

-node undirected skeleton. Numerical experiments illustrate the theoretical results by successfully separating orientations within a Markov equivalence class, which are indistinguishable by conditional independence alone.

Structural Equation Models Identifiability Semiparametric Framework Conditional Independence Family

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