Wang, D., Yu. Y. and Rinaldo, A. (2018). Optimal Covariance Change Point Detection in High Dimensions, arxiv.

Lauritzen, S., Rinaldo, A. and Sadeghi, K. (2017). On Exchangeability in Network Models, arxiv.

Wang. D., Lu, X. and Rinaldo, A. (2017). Optimal Rates for Cluster Tree Estimation using Kernel Density Estimators,  arxiv.

Kim., J., Shin, J., Rinaldo, A. and Wasserman, L. (2017). Confidence sets for persistent homology of the KDE filtration. pdf.

Kim, N. and Rinaldo, A. (2017). Community Detection on Ego Networks via Mutual Friend Counts. pdf.

Kim, N. and Rinaldo, A. (2017). Edge-Induced Sampling from Graphons. pdf.

Aamari, E., Kim, J., Chazal, F., Bertrand, M., Rinaldo, A., Wasserman, L. (2017). Estimating the Reach of a Manifold, arxiv.

Rinaldo, A., Wasserman,G’Sell, M., Jing, L. and Tibshirani, R. (2016). Bootstrapping and Sample Splitting For High-Dimensional, Assumption-Free Inference, arxiv.

Rinaldo, A., Lauritzen, S. and Sadeghi, K. (2016). On Exchangeability in Network Models. Available on request.

Sadeghi, K. and Rinaldo, A. (2016). Hierarchical Models for Independence Structures of Networks, arxiv.



Unpublished Manuscripts

Chen,Y.C., Wang, D., Rinaldo, A. and Wasserman, L. (2015). Statistical Analysis of Persistence Intensity Functions, arxiv.

Kent, B. P., Rinaldo, A. and Verstynen, T. (2013). DeBaCl: A Python Package for Interactive DEnsity-BAsed CLustering, arxiv. Download DeBaCl.

Balakrishnan, S., Narayanan, S., Rinaldo, A., Singh, A. and Wasserman, L. (2013). Tight Lower Bounds for Homology Inference, arxiv.

Rinaldo, A., Petrovíc, S. and Fienberg, S.E. (2010). On the Existence of the MLE for a Directed Random Graph Network Model with Reciprocation. arxiv

Rinaldo, A. (2006). Computing Maximum Likelihood Estimates in Log-Linear Models. Manuscript proposing computational procedures for extended maximum likelihood estimation (extracted from my Ph.D. thesis). draft pdf. A small MATLAB toolbox implementing some of the routines described in the document, which was written for testing purposes, is also available without any warranty!




Kim, J. Rinaldo, A. and Wasserman, L. (2018). Minimax Rates for Estimating the Dimension of a Manifold, to appear in Journal of Computational Geometry, arxiv.

Lauritzen, S.,  Rinaldo, A. and Sadeghi, K. (2018), Random Networks, Graphical Models, and Exchangeability (2018), to appear in the Journal of the Royal Statistical Society, Series B, arxiv.

Lin,  K., Sharpnack, J., Rinaldo, A. and Tibshirani, R.J. (2017). Approximate Recovery in Changepoint Problems, from ℓ2 Estimation Error Rates, NIPS 2017arxiv.

Tibshirani, R.J., Rinaldo, A., Tibshirani, R. and Wasserman, L. (2015).  Uniform Asymptotic Inference and the Bootstrap After Model Selection, to appear in the Annals of Statistics. arxiv.

Balakrishnan, S., Kolar, M., Rinaldo, A. and Singh, A. (2017). Recovering Block-structured Activations Using Compressive Measurements, to appear in the Electronic Journal of Statisticsarxiv.

Chazal, F., Fasy, B.T., Lecci, F., Michel, B., Rinaldo, A., Wasserman, L., (2015), Robust Topological Inference: Distance-to-a-Measure and Kernel Distance,  to appear in the Journal of Machine Learning Researcharxiv.

Lei, J., G’Sell, M., Rinaldo, A., Tibshirani, R. and Wasserman, L. (2016). Distribution-Free Predictive Inference For Regression, to appear in the Journal of the American Statistical Associationarxiv.

Kim, J., Chen, Y.-C, Balakrishnan, S., Rinaldo, A. and Wasserman, L. (2016). Statistical Inference for Cluster Trees, NIPS 2016arxiv.

Nicolas Kim, Dane Wilburne, Sonja Petrović, Alessandro Rinaldo (2015). On the Geometry and Extremal Properties of the Edge-Degeneracy Model, SDM16 Workshop on Mining Networks and Graphs (2016), arxiv.

Yin, M., Rinaldo, A. and Fadnavis S. (2015). Asymptotic quantization of exponential random graphs, the Annals of Applied Probability, 26(6), 3251-3285. arxiv.

Sharpnack, J.,  Rinaldo, A. and Singh, A. (2015). Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic, IEEE Transaction on Signal Processing, 64(2), 364-379, arxiv.

Chazal, F., Fasy, B.T., Lecci, F., Michel, B., Rinaldo, A. and Wasserman, L. (2015). Subsampling Methods for Persistent Homology, ICML 2015arxiv.

Lei, J. and Rinaldo, A. (2015). Consistency of Spectral Clustering in Sparse Stochastic Block Models, Annals of Statistics, 43(1), 215 – 237. arxiv.

Chazal, F., Fasy, B.T., Lecci, F., Rinaldo, A. and Wasserman, L. (2015). Stochastic Convergence of Persistence Landscapes and Silhouettes,  Journal of Computational Geometry, 6(2), 140-161.
The paper initially appeared in the Proceedings of the 30th Symposium of Computational Geometry (SoCG 2014)arxiv.

Sadeghi, K. and Rinaldo, A. (2014). Statistical Models for Degree Distributions of Networks, NIPS 2014 Workshop “From Graphs to Rich Data”, arxiv.

Stasi, D., Sadeghi, K., Rinaldo, A., Petrović, S. and Fienberg, S.E. (2014). $β$ models for random hypergraphs with a given degree sequence, COMPSTAT 2014, arxiv.

Wasserman, L., Kolar, M. and Rinaldo, A. (2014). Berry-Essen Bounds for Estimating Undirected Graphs, Electronic Journal of Statistics,  8(1), 1188-1224. pdfarxiv.

Yang, X., Rinaldo, A. and Fienberg, S.E. (2014). Estimation for Dyadic-Dependent Exponential Random Graph Models, the Journal of Algebraic Statistics, 5(1).

Fasy, B.T., Lecci, F., Rinaldo, A., Wasserman, L., Balakrishnan, S. and Singh, A. (2014). Confidence Sets for Persistence Diagrams,  The Annals of Statistics, 42(6), 2301–2339. arxiv.

Lecci, F., Rinaldo, A. and Wasserman, L. (2014). Statistical Analysis of Metric Graph Reconstruction, Journal of Machine Learning Research, 15, 3425-3446. arxiv.

Kent, B. P., Rinaldo, A., Yeh, F.-C. and Verstynen, T. (2014). Mapping Topographic Structure in White Matter Pathways with Level Set Trees, PLOS One, link.

Chazal, F., Fasy, B. T., Lecci, F., Rinaldo, A., Singh, A., Wasserman L. (2013). On the Bootstrap for Persistence Diagrams and Landscapes, Modeling and Analysis of Information Systems, 20:6, 96–105. arxiv.

Balakrishnan, S., Narayanan, S., Rinaldo, A., Singh, A. and Wasserman (2013). Cluster Trees on Manifolds, NIPS 2013. pdf.

Lei, J., Rinaldo, A. and Wasserman, L. (2013). A Conformal Prediction Approach to Explore Functional Data, to appear in Annals of Mathematics and Artificial Intelligence, arxiv.

Poczos, B., Rinaldo, A., Singh, A. and Wasserman, L. (2013). Distribution-Free Distribution Regression, AISTATS 2013. pdf

Sharpnak, J., Rinaldo, A. and Singh, A. (2013). Changepoint Detection over Graphs with the Spectral Scan Statistic, AISTATS 2013. pdf

Rinaldo, A., Petrovíc, S. and Fienberg, S.E.  (2013). Maximum Likelihood Estimation in Network Models, Annals of Statistics, 41(3), 1085-1110. arxivR code

Hall, R., Rinaldo, A. and Wasserman, L. (2013). Differential Privacy for Functions and Functional Data,  Journal of Machine Learning Research, 14, 703-727. pdf

Shalizi, C. R. and Rinaldo, A. (2013). Consistency under Sampling of Exponential Random Graph Models, Annals of Statistics, 41(2), 508–535. pdf of the paper and pdf of the supplementary material

Rinaldo, A., Petrovíc, S. and Fienberg, S.E. (2012). How Does Maximum Likelihood Estima- tion for the p1 Model Scale for Large Sparse Networks?, NIPS 2012 workshop on Algorithmic and Statistical Approaches for Large Social Network Data Sets.

Hall, R., Rinaldo, A. and Wasserman, L. (2012). Random Differential Privacy,  Journal of Privacy and Confidentiality, 4(2), 43–59. pdf

Rinaldo, A., Singh, A., Nugent, R. and Wasserman, L. (2012). Stability of Density-Based Clustering,  Journal of Machine Learning, 13, 905–948. pdf

Fienberg, S.E. and  Rinaldo, A. (2012). Maximum Likelihood Estimation in Log-linear Models, Annals of Statistics, 40(2), 996–1023. pdf of the paper and pdf of the supplementary material. The original version of the manuscript appeared on the arxiv under the title “Maximum Likelihood Estimation in Log-linear Models: Theory and Algorithms.”

Balakrishnan, S., Rinaldo, A., Sheehy, D. R., Singh, A. and Wasserman, L. (2012). Minimax Rates for Homology Inference, AISTATS 2012. arxiv

Sharpnack, J.,  Rinaldo, A. and Singh, A. (2012). Sparsistency of the Edge Lasso over Graphs, AISTATS 2012. pdf

Nardi, Y. and Rinaldo, A. (2012). The Log-linear Group Lasso Estimator for Hierarchical Log-Linear Models and Its Asymptotic Properties, Bernoulli, 18(3), 945-974pdf. For a longer version see this pdf

Yang, X., Fienberg, S.E. and Rinaldo, A. (2012). Differential Privacy for Protecting Multi-dimensional Contingency Table Data: Extensions and Applications,  Journal of Privacy and Confidentiality, 4(1), 101-125. pdf

Balakrishnan,  S., Kolar, M., Rinaldo, A., Singh, A. and Wasserman, L. (2011). Statistical and computational tradeoffs in biclustering, NIPS 2011 Workshop on Computational Trade-offs in Statistical Learning. pdf

Kolar, M., Balakrishnan,  S., Rinaldo, A. and Singh, A. (2011). Minimax Localization of Structural Information in Large Noisy Matrices, Neural Information Processing Systems, NIPS 2011. pdf

Nardi, Y. and Rinaldo, A. (2011). Autoregressive Process Modeling via the Lasso Procedure, Journal of Multivariate Analysis, 103(3), 528–549. pdf

Fienberg, S.E., Rinaldo, A. and Yang, X. (2011). Differential Privacy and the Risk-Utility Tradeoff for Multi-dimensional Contingency Tables, Lecture Notes in Computer Science,2011, Volume 6344, 187–199, Springer. pdf

Rinaldo, A. and Wasserman, L. (2010). Generalized Density Clustering, The Annals of Statistics, 38(5), 2678–2722. pdf

Petrovíc, S., Rinaldo, A. and Fienberg, S.E. (2009). Algebraic Statistics for a Directed Random Graph Model with Reciprocation, Algebraic Methods in Statistics and Probability II, Contemporary Mathematics series, published by the American Mathematical Society. pdf

Fienberg, S.E., Petrovíc, S. and Rinaldo, A. (2009). Algebraic Statistics for p_1 Random Graphs Models: Markov Bases and their Uses,  “Looking back: A festschrift to Honor Paul Holland”,  published by the Educational Testing Services.

Rinaldo, A. (2009). Properties and Refinement of the Fused Lasso, The Annals of Statistics 37, 5B, 2922–2952. pdf. Correction.

Rinaldo, A., Fienberg, S.E. and Zhou, Y. (2009). On the Geometry of Discrete Exponential Families with Application to Exponential Random Graph  Models,   Electronic Journal of Statistics, 3, 446–484. pdf MATLAB scripts and GUI

Nardi, Y. and Rinaldo, A. (2008). On the Asymptotic Properties of The Group Lasso Estimator in Least Squares Problem, Electronic Journal of Statistics, 2, 605–633. pdf

Dobra, A., Fienberg, S.E., Rinaldo, A., Slavkovic, A. and Zhou, Y. (2008). Algebraic Statistics and Contingency Table Problems: Estimation and Disclosure Limitation,  in Emerging Applications of Algebraic Geometry, (M. Putinar, S. Sullivant, eds.), IMA Series in Applied Mathematics, Springer-Verlag. pdf

Fienberg, S.E., Hersh, P., Rinaldo, A. and Zhou, Y. (2007). Maximum Likelihood Estimation in Latent Class Models For Contingency Table Data, in  Algebraic and Geometric Methods in Statistics, Cambridge University Press. pdf

Fienberg, S. E., Rinaldo, A. (2007). Three Centuries of Categorical Data Analysis: Log-linear Models and Maximum Likelihood Estimation,  Journal of Statistical Planning and Inference, 137, 11, 3420-3445. Special Issue: In Celebration of the Centennial of The Birth of Samarendra Nath Roy (1906-1964). pdf

Eriksson, N., Fienberg, E. S., Rinaldo, A., Sullivant, S. (2006). Polyhedral Conditions for the Nonexistence of the MLE for Hierarchical Log-linear Models, Journal of Symbolic Computation, 41, 222–233. Special Issue on Algebraic Statistics. pdf

Rinaldo, A., Balcanu, S., Devlin, B., Sonpar, V., Wasserman, L., Roeder, K. (2005). Characterization of Multilocus Linkage Disequilibrium, Genetic Epidemiology, 28 (3), 193–206. pdf and poster version