Items where department is "Statistics"

University Structure (106352) LSE (106352) Academic Departments (62972) Statistics (1721)
Number of items: 99.
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  • Bynum, Lucius E.J., Loftus, Joshua R., Stoyanovich, Julia (2023). Counterfactuals for the future. In Williams, B., Chen, Y. & Neville, J. (Eds.), AAAI-23 Special Tracks (pp. 14144-14152). AAAI Press. https://doi.org/10.1609/aaai.v37i12.26655
  • Chen, Yunxiao, Xu, Gongjun (2023). Yunxiao Chen and Gongjun Xu's contribution to the discussion of ‘Vintage factor analysis with Varimax performs statistical inference’ by Rohe & Zeng. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 85(4), 1082 – 1084. https://doi.org/10.1093/jrsssb/qkad040
  • Divasón, Jose, Mohammadi, Fatemeh, Saenz-De-Cabezon, Eduardo, Wynn, Henry (2023). Sensitivity analysis of discrete preference functions using Koszul simplicial complexes. In Jeronimo, G. (Ed.), ISSAC 2023 - Proceedings of the 2023 International Symposium on Symbolic and Algebraic Computation (pp. 227-235). Association for Computing Machinery. https://doi.org/10.1145/3597066.3597095
  • Goracci, Greta, Giannerini, Simone, Chan, Kung Sik, Tong, Howell (2023). Testing for threshold effects in the Tarma framework. Statistica Sinica, 33(3), 1879-1901. https://doi.org/10.5705/ss.202021.0120
  • Lee, Dabeen, Vojnovic, Milan, Yun, Se-young (2023). Test score algorithms for budgeted stochastic utility maximization. INFORMS Journal on Optimization, 5(1), 27 - 67. https://doi.org/10.1287/ijoo.2022.0075
  • Li, Jing-Jing, Shi, Chengchun, Li, Lexin, Collins, Anne G.E. (2023-07-26 - 2023-07-29) A generalized method for dynamic noise inference in modeling sequential decision-making [Paper]. Cognition in context, International Convention Centre Sydney, Sydney, Australia, AUS. [In Press]
  • Luo, Yuanyuan (2023). Comparing recurrent neural network with GARCH model on forecasting volatility based on SSE 50ETF. In Dai, W. & Jin, S. (Eds.), Second International Conference on Statistics, Applied Mathematics, and Computing Science, CSAMCS 2022 . Society of Photo-optical Instrumentation Engineers. https://doi.org/10.1117/12.2673039
  • Luo, Yuanyuan (2023). Using GARCH family models estimate the volatility of SSE 50ETF. In Dai, W. & Jin, S. (Eds.), Second International Conference on Statistics, Applied Mathematics, and Computing Science, CSAMCS 2022 . Society of Photo-optical Instrumentation Engineers. https://doi.org/10.1117/12.2671961
  • Vojnović, Milan, Yun, Se-young, Zhou, Kaifang (2023). Accelerated MM algorithms for inference of ranking scores from comparison data. Operations Research, 71(4), 1318 - 1342. https://doi.org/10.1287/opre.2022.2264
  • Wen, Le, Guang, Fengtao, Wang, Yiqing, Sharp, Basil (2023). Decarbonization in New Zealand–where and how: a combination of input–output approach and structural decomposition analysis. New Zealand Economic Papers, https://doi.org/10.1080/00779954.2023.2196676
  • Yi, Jialin, Vojnović, Milan (2023). On regret-optimal cooperative nonstochastic multi-armed bandits. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, 2023-M, 1329-1335. https://doi.org/10.5555/3545946.3598780
  • Çetin, Umut, Waelbroeck, Henri (2023). Power laws in market microstructure. In Jarrow, R. A. & Madan, D. B. (Eds.), Peter Carr Gedenkschrift: Research Advances in Mathematical Finance (pp. 753 - 819). World Scientific (Firm). https://doi.org/10.1142/9789811280306_0022
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  • Aschermayr, Patrick (2023). Sequential Bayesian learning for State Space Models [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004578
  • Atkinson, Anthony C., Duarte, Belmiro P.M., Pedrosa, David, van Munster, Marlena (2023). Randomizing a clinical trial in neuro-degenerative disease. Contemporary Clinical Trials Communications, 33, https://doi.org/10.1016/j.conctc.2023.101140 picture_as_pdf
  • Barreto, Marcos (13 June 2023) A fundamental problem at the heart of data science teaching. LSE Higher Education Blog. picture_as_pdf
  • Baurdoux, Erik J., Pedraza, José M. (2023). Predicting the last zero before an exponential time of a spectrally negative Lévy process. Advances in Applied Probability, 55(2), 611 - 642. https://doi.org/10.1017/apr.2022.47 picture_as_pdf
  • Bonnier, Patric, Oberhauser, Harald, Szabo, Zoltan (2023). Kernelized cumulants: beyond kernel mean embeddings. In Advances in Neural Information Processing Systems 36 . Curran Associates, Inc.. picture_as_pdf
  • Bottazzi, Giulio, Cordoni, Francesco, Livieri, Giulia, Marmi, Stefano (2023). Uncertainty in firm valuation and a cross-sectional misvaluation measure. Annals of Finance, 19(1), 63 - 93. https://doi.org/10.1007/s10436-022-00423-w picture_as_pdf
  • Cai, Hanqing, Wang, Tengyao (2023). Estimation of high-dimensional change-points under a group sparsity structure. Electronic Journal of Statistics, 17(1), 858 – 894. https://doi.org/10.1214/23-EJS2116 picture_as_pdf
  • Cai, Hengrui, Shi, Chengchun, Song, Rui, Lu, Wenbin (2023). Jump interval-learning for individualized decision making with continuous treatments. Journal of Machine Learning Research, picture_as_pdf
  • Caron, François, Panero, Francesca, Rousseau, Judith (2023). On sparsity, power-law, and clustering properties of graphex processes. Advances in Applied Probability, 55(4), 1211 - 1253. https://doi.org/10.1017/apr.2022.75 picture_as_pdf
  • Chang, Jinyuan, Chen, Cheng, Qiao, Xinghao, Yao, Qiwei (2023). An autocovariance-based learning framework for high-dimensional functional time series. Journal of Econometrics, 239(2). https://doi.org/10.1016/j.jeconom.2023.01.007 picture_as_pdf
  • Chang, Jinyuan, Zhang, Henry, Yang, Lin, Yao, Qiwei (2023). Modelling matrix time series via a tensor CP-decomposition. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 85(1), 127 – 148. https://doi.org/10.1093/jrsssb/qkac011 picture_as_pdf
  • Chen, Yining, S. Torrent, Hudson, A. Ziegelmann, Flavio (2023). Robust nonparametric frontier estimation in two steps. Econometric Reviews, 42(7), 612 - 634. https://doi.org/10.1080/07474938.2023.2219183 picture_as_pdf
  • Chen, Yunxiao, Li, Chengcheng, Ouyang, Jing, Xu, Gongjun (2023). DIF statistical inference without knowing anchoring items. Psychometrika, 88(4), 1097 - 1122. https://doi.org/10.1007/s11336-023-09930-9 picture_as_pdf
  • Chen, Yunxiao, Li, Chengcheng, Ouyang, Jing, Xu, Gongjun (2023). Statistical inference for noisy incomplete binary matrix. Journal of Machine Learning Research, 24, picture_as_pdf
  • Chen, Yunxiao, Li, Xiaoou (2023). Compound sequential change-point detection in parallel data streams. Statistica Sinica, 33(1), 453 - 474. https://doi.org/10.5705/ss.202020.0508 picture_as_pdf
  • Chen, Zezhun (2023). Point processes and integer-valued time series [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004552
  • Chen, Zezhun Chen, Dassios, Angelos, Tzougas, George (2023). INAR approximation of bivariate linear birth and death process. Journal of Applied Statistics, 26(3), 459 - 497. https://doi.org/10.1007/s11203-023-09289-9 picture_as_pdf
  • Chen, Zezhun Chen, Dassios, Angelos, Tzougas, George (2023). A first order binomial mixed poisson integer-valued autoregressive model with serially dependent innovations. Journal of Applied Statistics, 50(2), 352 - 369. https://doi.org/10.1080/02664763.2021.1993798 picture_as_pdf
  • Chiang, Daryl, Kotecha, Meena (2023-09-04 - 2023-09-07) Reducing mathematics anxiety by enhancing mathematical resilience - a mindset intervention [Poster]. RSS International Conference 2023, Harrogate Convention Centre, Harrogate, United Kingdom, GBR. picture_as_pdf
  • Cárdenas Hurtado, Camilo Alberto (2023). Generalised latent variable models for location, scale, and shape parameters [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004531
  • Dadush, Daniel, Koh, Zhuan Khye, Natura, Bento, Végh, László A. (2023). An accelerated Newton–Dinkelbach method and its application to two variables per inequality systems. Mathematics of Operations Research, 48(4), 1934 - 1958. https://doi.org/10.1287/moor.2022.1326 picture_as_pdf
  • Dassios, Angelos, Zhang, Junyi (2023). Exact simulation of Poisson-Dirichlet distribution and generalised gamma process. Methodology and Computing in Applied Probability, 25(2). https://doi.org/10.1007/s11009-023-10040-3 picture_as_pdf
  • Di Mari, Roberto, Bakk, Zsuzsa, Oser, Jennifer, Kuha, Jouni (2023). A two-step estimator for multilevel latent class analysis with covariates. Psychometrika, 88(4), 1144 - 1170. https://doi.org/10.1007/s11336-023-09929-2 picture_as_pdf
  • Duarte, Belmiro P.M., Atkinson, Anthony C., Oliveira, Nuno M.C. (2023). Optimum design for ill-conditioned models: K–optimality and stable parameterizations. Chemometrics and Intelligent Laboratory Systems, 239, https://doi.org/10.1016/j.chemolab.2023.104874 picture_as_pdf
  • Duarte, Belmiro P.M., Atkinson, Anthony C., P. Singh, Satya, S. Reis, Marco (2023). Optimal design of experiments for hypothesis testing on ordered treatments via intersection-union tests. Statistical Papers, 64(2), 587 - 615. https://doi.org/10.1007/s00362-022-01334-8 picture_as_pdf
  • Feinstein, Zachary, Sojmark, Andreas (2023). Contagious McKean–Vlasov systems with heterogeneous impact and exposure. Finance and Stochastics, 27(3), 663 - 711. https://doi.org/10.1007/s00780-023-00504-2 picture_as_pdf
  • Fryzlewicz, Piotr (2023). Narrowest Significance Pursuit: inference for multiple change-points in linear models. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2023.2211733 picture_as_pdf
  • Gao, Yuhe, Shi, Chengchun, Song, Rui (2023). Deep spectral Q-learning with application to mobile health. Stat, 12(1). https://doi.org/10.1002/sta4.564 picture_as_pdf
  • Gavioli-Akilagun, Shakeel (2023). On inference and causality in change point regressions [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004764
  • Ge, Lin, Wang, Jitao, Shi, Chengchun, Wu, Zhenke, Song, Rui (2023). A reinforcement learning framework for dynamic mediation analysis. Proceedings of Machine Learning Research, 202, 11050 - 11097. picture_as_pdf
  • Guastadisegni, Lucia, Moustaki, Irini, Vasdekis, Vassilis, Cagnone, Silvia (2023). Detecting latent variable non-normality through the generalized Hausman test. In Wiberg, M., Molenaar, D., González, J., Kim, J. & Hwang, H. (Eds.), Quantitative Psychology - The 87th Annual Meeting of the Psychometric Society, 2022 (pp. 107-118). Springer Netherlands. https://doi.org/10.1007/978-3-031-27781-8_10 picture_as_pdf
  • Guo, Shaojun, Qiao, Xinghao (2023). On consistency and sparsity for high-dimensional functional time series with application to autoregressions. Bernoulli, 29(1), 451 - 472. https://doi.org/10.3150/22-BEJ1464 picture_as_pdf
  • Hana, Yuefeng, Chenb, Rong, Zhangb, Cun-Hui, Yao, Qiwei (2023). Simultaneous decorrelation of matrix time series. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2022.2151448 picture_as_pdf
  • Hansen, Sakina, Loftus, Joshua (2023). Model-agnostic auditing a lost cause? CEUR Workshop Proceedings, 3442, picture_as_pdf
  • Jang, Jiwook, Qu, Yan, Zhao, Hongbiao, Dassios, Angelos (2023). A Cox model for gradually disappearing events. Probability in the Engineering and Informational Sciences, 37(1), 214 - 231. https://doi.org/10.1017/S0269964821000553 picture_as_pdf
  • Jiang, Binyan, Li, Jialiang, Yao, Qiwei (2023). Autoregressive networks. Journal of Machine Learning Research, picture_as_pdf
  • Kalinke, Florian, Szabo, Zoltan (2023). Nyström M-Hilbert-Schmidt independence criterion. Proceedings of Machine Learning Research, 216, 1005-1015. picture_as_pdf
  • Kotecha, Meena (2023). How can educators prevent the development of mathematics anxiety? Research for the World, picture_as_pdf
  • Kuha, Jouni, Zhang, Siliang, Steele, Fiona (2023). Latent variable models for multivariate dyadic data with zero inflation: analysis of intergenerational exchanges of family support. Annals of Applied Statistics, 17(2), 1521 - 1542. https://doi.org/10.1214/22-AOAS1680 picture_as_pdf
  • Li, Ting, Shi, Chengchun, Wang, Jianing, Zhou, Fan, Zhu, Hongtu (2023). Optimal treatment allocation for efficient policy evaluation in sequential decision making. In Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (Eds.), Advances in Neural Information Processing Systems 36 (NeurIPS 2023) . Neural Information Processing Systems Foundation. picture_as_pdf
  • Lillo, Fabrizio, Livieri, Giulia, Marmi, Stefano, Solomko, Anton, Vaienti, Sandro (2023). Analysis of bank leverage via dynamical systems and deep neural networks. SIAM Journal on Financial Mathematics, 14(2), 598 - 643. https://doi.org/10.1137/21M1412517 picture_as_pdf
  • Lillo, Fabrizio, Livieri, Giulia, Marmi, Stefano, Solomko, Anton, Vaienti, Sandro (2023). Unimodal maps perturbed by heteroscedastic noise: an application to a financial systems. Journal of Statistical Physics, 190(10). https://doi.org/10.1007/s10955-023-03160-0 picture_as_pdf
  • Liu, Naijia, Kotecha, Meena (2023-09-04 - 2023-09-07) The relationship between undergraduate students’ mathematics anxiety and motivation to learn mathematics: a mixed method study [Poster]. RSS International Conference 2023, Harrogate Convention Centre, Harrogate, United Kingdom, GBR. picture_as_pdf
  • Liu, Xinyi Lin, Wallin, Gabriel, Chen, Yunxiao, Moustaki, Irini (2023). Rotation to sparse loadings using Lp losses and related inference problems. Psychometrika, 88(2), 527 - 553. https://doi.org/10.1007/s11336-023-09911-y picture_as_pdf
  • Liu, Yirui, Qiao, Xinghao, Wang, Liying, Lam, Jessica (2023). EEGNN: edge enhanced graph neural network with a Bayesian nonparametric graph model. Proceedings of Machine Learning Research, 206, 2132-2146. picture_as_pdf
  • Loftus, Joshua R. (2023). It’s about time: counterfactual fairness and temporal depth. CEUR Workshop Proceedings, 3442, picture_as_pdf
  • Luo, Yu, Graham, Daniel J., McCoy, Emma J. (2023). Semiparametric Bayesian doubly robust causal estimation. Journal of Statistical Planning and Inference, 225, 171 - 187. https://doi.org/10.1016/j.jspi.2022.12.005 picture_as_pdf
  • Maeng, Hyeyoung, Fryzlewicz, Piotr (2023). Detecting linear trend changes in data sequences. Statistical Papers, 16, https://doi.org/10.1007/s00362-023-01458-5 picture_as_pdf
  • Maruri-Aguilar, Hugo, Wynn, Henry (2023). Sparse polynomial prediction. Statistical Papers, 64(4), 1233 - 1249. https://doi.org/10.1007/s00362-023-01439-8 picture_as_pdf
  • Mavridis, Dimitris, Nikolakopoulou, Adriani, Moustaki, Irini, Chaimani, Anna, Porcher, Raphaël, Boutron, Isabelle, Ravaud, Philippe (2023). Considering multiple outcomes with different weights informed the hierarchy of interventions in network meta-analysis. Journal of Clinical Epidemiology, 154, 188-196. https://doi.org/10.1016/j.jclinepi.2022.12.025 picture_as_pdf
  • Nasir, Nida, Kansal, Afreen, Alshaltone, Omar, Barneih, Feras, Shanableh, Abdallah, Al-Shabi, Mohammad, Al Shammaa, Ahmed (2023). Deep learning detection of types of water-bodies using optical variables and ensembling. Intelligent Systems with Applications, 18, https://doi.org/10.1016/j.iswa.2023.200222 picture_as_pdf
  • Papadimitriou, Dimitris, Tokis, Konstantinos, Vichos, Georgios, Mourdoukoutas, Panos (2023). Managing other people's money: an agency theory in financial management industry. Journal of Financial Research, https://doi.org/10.1111/jfir.12344 picture_as_pdf
  • Qu, Yan, Dassios, Angelos, Zhao, Hongbiao (2023). Shot-noise cojumps: exact simulation and option pricing. Journal of the Operational Research Society, 74(3), 647 - 665. https://doi.org/10.1080/01605682.2022.2077660 picture_as_pdf
  • Riani, Marco, Atkinson, Anthony C., Corbellini, Aldo (2023). Automatic robust Box-Cox and extended Yeo-Johnson transformations in regression. Statistical Methods and Applications, 32(1), 75 - 102. https://doi.org/10.1007/s10260-022-00640-7 picture_as_pdf
  • Riani, Marco, Atkinson, Anthony C., Corbellini, Aldo (2023). Robust response transformations for generalized additive models via additivity and variance stabilization. In Grilli, L., Lupparelli, M., Rampichini, C., Rocco, E. & Vichi, M. (Eds.), Statistical Models and Methods for Data Science (pp. 147 - 159). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-30164-3_12 picture_as_pdf
  • Rosenblatt, Lucas, Herman, Bernease, Holovenko, Anastasia, Lee, Wonkwon, Loftus, Joshua, McKinnie, Elizabeth, Rumezhak, Taras, Stadnik, Andrii, Howe, Bill, Stoyanovich, Julia (2023). Epistemic parity: reproducibility as an evaluation metric for differential privacy. Proceedings of the VLDB Endowment, 16(11), 3178 – 3191. https://doi.org/10.14778/3611479.3611517 picture_as_pdf
  • Rudas, Tamás, Bergsma, Wicher (2023). Marginal models: an overview. In Kateri, M. & Moustaki, I. (Eds.), Trends and Challenges in Categorical Data Analysis: Statistical Modelling and Interpretation (pp. 67 - 115). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-31186-4_3 picture_as_pdf
  • Sabharwal, Ragvir Singh (2023). On factor models for high-dimensional time series [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004503
  • Shen, Tonggaochuan, Cheng, Long, Yang, Yongjiang, Deng, Jialin, Jin, Tanhua, Cao, Mengqiu (2023). Do residents living in transit-oriented development station catchment areas travel more sustainably? The impacts of life events. Journal of Advanced Transportation, 2023, https://doi.org/10.1155/2023/9318505 picture_as_pdf
  • Shi, Chengchun, Qi, Zhengling, Wang, Jianing, Zhou, Fan (2023). Value enhancement of reinforcement learning via efficient and robust trust region optimization. Journal of the American Statistical Association, 1-15. https://doi.org/10.1080/01621459.2023.2238942 picture_as_pdf
  • Shi, Chengchun, Wan, Runzhe, Song, Ge, Luo, Shikai, Zhu, Hongtu, Song, Rui (2023). A multiagent reinforcement learning framework for off-policy evaluation in two-sided markets. Annals of Applied Statistics, 17(4), 2701 - 2722. https://doi.org/10.1214/22-AOAS1700 picture_as_pdf
  • Strong, Peter, Shenvi, Aditi, Yu, Xuewen, Papamichail, K. Nadia, Wynn, Henry P., Smith, Jim Q. (2023). Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies. Journal of the Operational Research Society, 74(2), 476 - 488. https://doi.org/10.1080/01605682.2021.2023673 picture_as_pdf
  • Suh, Ellie, James, H. (2023). The social, cultural and economic influences on retirement saving for young adults in the UK. In Hofäcker, D. & Kuitto, K. (Eds.), Youth employment insecurity and pension adequacy (pp. 127–145). Edward Elgar. picture_as_pdf
  • Uehara, Masatoshi, Kiyohara, Haruka, Bennett, Andrew, Chernozhukov, Victor, Jiang, Nan, Kallus, Nathan, Shi, Chengchun, Sun, Wenguang (2023). Future-dependent value-based off-policy evaluation in POMDPs. In Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (Eds.), Advances in Neural Information Processing Systems 36 (NeurIPS 2023) . Neural Information Processing Systems Foundation. picture_as_pdf
  • Vamvourellis, Konstantinos, Kalogeropoulos, Konstantinos, Moustaki, Irini (2023). Assessment of generalised Bayesian structural equation models for continuous and binary data. British Journal of Mathematical and Statistical Psychology, 76(3), 559 - 584. https://doi.org/10.1111/bmsp.12314 picture_as_pdf
  • Wallin, Gabriel, Wiberg, Marie (2023). Model misspecification and robustness of observed-score test equating using propensity scores. Journal of Educational and Behavioral Statistics, 48(5), 603 - 635. https://doi.org/10.3102/10769986231161575 picture_as_pdf
  • Wang, Jitao, Shi, Chengchun, Wu, Zhenke (2023). A robust test for the stationarity assumption in sequential decision making. Proceedings of Machine Learning Research, 36355-36379. picture_as_pdf
  • Wu, Guojun, Song, Ge, Lv, Xiaoxiang, Luo, Shikai, Shi, Chengchun, Zhu, Hongtu (2023). DNet: distributional network for distributional individualized treatment effects. Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023, 5215 - 5224. https://doi.org/10.1145/3580305.3599809 picture_as_pdf
  • Wu, Qianxin, Wu, Junjing, Abdul Karim, Muhammad Kaiser, Chen, Xi, Wang, Tengyao, Iwama, Sho, Carobbio, Stefania, Keen, Peter, Vidal-Puig, Antonio & Kotter, Mark R. et al (2023). Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons. Molecular Cell, 83(7), 1125 - 1139. https://doi.org/10.1016/j.molcel.2023.02.011 picture_as_pdf
  • Xie, Zilong, Chen, Yunxiao, von Davier, Matthias, Weng, Haolei (2023). Variable selection in latent variable models via knockoffs: an application to international large-scale assessment in education. Journal of the Royal Statistical Society. Series A: Statistics in Society, https://doi.org/10.1093/jrsssa/qnad137 picture_as_pdf
  • Xu, Yang, Zhu, Jin, Shi, Chengchun, Luo, Shikai, Song, Rui (2023). An instrumental variable approach to confounded off-policy evaluation. Proceedings of Machine Learning Research, 202, 38848 - 38880. picture_as_pdf
  • Yang, Shuhan (2023). Tools for model selection for mean-nonstationary time series [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004630
  • Yi, Jialin (2023). Regret-minimization algorithms for multi-agent cooperative learning systems [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004523
  • Yi, Jialin, Vojnović, Milan (2023). Doubly adversarial federated bandits. Proceedings of Machine Learning Research, 39951 - 39967. picture_as_pdf
  • Yousefi, Elham, Pronzato, Luc, Hainy, Markus, Müller, Werner G., Wynn, Henry P. (2023). Discrimination between Gaussian process models: active learning and static constructions. Statistical Papers, 64(4), 1275 - 1304. https://doi.org/10.1007/s00362-023-01436-x picture_as_pdf
  • Zhang, Bo, Pan, Guangming, Yao, Qiwei, Wang, Jian-Zhou (2023). Factor modelling for clustering high-dimensional time series. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2023.2183132 picture_as_pdf
  • Zhang, Junyi, Dassios, Angelos (2023). Truncated Poisson-Dirichlet approximation for Dirichlet process hierarchical models. Statistics and Computing, picture_as_pdf
  • Zhang, Junyi, Dassios, Angelos (2023). Truncated two-parameter Poisson-Dirichlet approximation for Pitman-Yor process hierarchical models. Scandinavian Journal of Statistics, https://doi.org/10.1111/sjos.12688 picture_as_pdf
  • Zhang, Wen, Shi, Jingwen, Wang, Xiaojun, Wynn, Henry (2023). AI-powered decision-making in facilitating insurance claim dispute resolution. Annals of Operations Research, https://doi.org/10.1007/s10479-023-05631-9 picture_as_pdf
  • Zhang, Xinyu, Li, Dong, Tong, Howell (2023). On the least squares estimation of multiple-threshold-variable autoregressive models. Journal of Business and Economic Statistics, https://doi.org/10.1080/07350015.2023.2174124 picture_as_pdf
  • Zhang, Yingying, Shi, Chengchun, Luo, Shikai (2023). Conformal off-policy prediction. Proceedings of Machine Learning Research, 206, 2751-2768. picture_as_pdf
  • Zhou, Kaifang (2023). Statistical inference for some choice models [Doctoral thesis]. London School of Economics and Political Science. https://doi.org/10.21953/lse.00004515
  • Zhou, Yunzhe, Qi, Zhengling, Shi, Chengchun, Li, Lexin (2023). Optimizing pessimism in dynamic treatment regimes: a Bayesian learning approach. Proceedings of Machine Learning Research, 206, picture_as_pdf
  • Zhou, Yunzhe, Shi, Chengchun, Li, Lexin, Yao, Qiwei (2023). Testing for the Markov property in time series via deep conditional generative learning. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 85(4), 1204 - 1222. https://doi.org/10.1093/jrsssb/qkad064 picture_as_pdf
  • van der Ark, L. Andries, Bergsma, Wicher P., Koopman, Letty (2023). Maximum augmented empirical likelihood estimation of categorical marginal models for large sparse contingency tables. Psychometrika, 88(4), 1228 - 1248. https://doi.org/10.1007/s11336-023-09932-7 picture_as_pdf
  • Çetin, Umut, Larsen, Kasper (2023). Uniqueness in cauchy problems for diffusive real-valued strict local martingales. Transactions of the American Mathematical Society Series B, 10(13), 381-406. https://doi.org/10.1090/btran/141 picture_as_pdf
  • Çetin, Umut, Waelbroeck, Henri (2023). Power laws in market microstructure. Frontiers of Mathematical Finance, 2(1), 56 - 98. https://doi.org/10.3934/fmf.2023003 picture_as_pdf