Pinboard (cshalizi)

Pinboard (cshalizi) https://pinboard.in/u:cshalizi/public/ recent bookmarks from cshalizi [2306.01129] White-Box Transformers via Sparse Rate Reduction 2023-06-05T15:12:58+00:00 https://arxiv.org/abs/2306.01129 cshalizi in_NB large_language_models_(so_called) neural_networks sparsity re:large_language_models_in_statistical_perspective https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9a2c882b1b03/ [2110.05518] Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs 2023-05-27T16:28:22+00:00 https://arxiv.org/abs/2110.05518 cshalizi neural_networks sparsity convexity optimization in_NB have_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2c84a4be8565/ Journal of Open Source Software: haldensify: Highly adaptive lasso conditional density estimation in R 2022-12-09T20:04:28+00:00 https://joss.theoj.org/papers/10.21105/joss.04522 cshalizi density_estimation R lasso sparsity van_der_laan.mark in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d6b76808e7da/ LASSO-driven inference in time and space 2021-08-10T14:07:16+00:00 https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-3/LASSO-driven-inference-in-time-and-space/10.1214/20-AOS2019.short cshalizi to:NB lasso sparsity regression time_series spatial_statistics variable_selection statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:86f9e897007b/ On cross-validated Lasso in high dimensions 2021-08-09T16:26:22+00:00 https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-3/On-cross-validated-Lasso-in-high-dimensions/10.1214/20-AOS2000.short cshalizi to:NB cross-validation lasso sparsity high-dimensional_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:25ec0744b249/ [2006.11908] Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis 2021-07-27T12:34:42+00:00 https://arxiv.org/abs/2006.11908 cshalizi to:NB factor_analysis sparsity model_selection carvalho.carlos_m. statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5efda0efeedf/ PsyArXiv Preprints | The Confidence Interval that Wasn’t: Bootstrapped “Confidence Intervals” in L1-Regularized Partial Correlation Networks 2021-07-19T13:52:15+00:00 https://psyarxiv.com/kjh2f cshalizi to:NB sparsity model_selection graphical_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f65b9477b29f/ [2107.03975] Compressibility Analysis of Asymptotically Mean Stationary Processes 2021-07-11T05:55:06+00:00 https://arxiv.org/abs/2107.03975 cshalizi to:NB stochastic_processes sparsity approximation ergodic_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:485fccb044e3/ [2105.02071] The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters 2021-05-06T13:50:57+00:00 https://arxiv.org/abs/2105.02071 cshalizi to:NB causal_inference model_selection sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c2156cc8eff6/ Consistent Sparse Deep Learning: Theory and Computation: Journal of the American Statistical Association: Vol 0, No 0 2021-04-21T16:09:37+00:00 https://www.tandfonline.com/doi/full/10.1080/01621459.2021.1895175 cshalizi neural_networks nonparametrics sparsity bayesian_consistency in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:eaf86c3cae34/ [2103.03191] Generalization Bounds for Sparse Random Feature Expansions 2021-04-21T14:53:40+00:00 https://arxiv.org/abs/2103.03191 cshalizi sparsity random_features approximation learning_theory to_teach:childs_garden_of_statistical_learning_theory in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:dde4a10d084c/ [1802.08667] De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers 2021-04-14T14:48:58+00:00 https://arxiv.org/abs/1802.08667 cshalizi to:NB causal_inference sparsity nonparametrics to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:56b3f2bb1d9f/ [1908.04904] Least Squares Approximation for a Distributed System 2021-04-14T14:47:32+00:00 https://arxiv.org/abs/1908.04904 cshalizi to:NB distributed_systems linear_regression sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:15c67296b489/ Phys. Rev. E 103, 042310 (2021) - Learning physically consistent differential equation models from data using group sparsity 2021-04-14T14:43:26+00:00 https://journals.aps.org/pre/abstract/10.1103/PhysRevE.103.042310 cshalizi statistical_inference_for_stochastic_processes equations_of_motion_from_a_time_series sparsity in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e7bbb81e3bd3/ Finding Distributed Needles in Neural Haystacks | Journal of Neuroscience 2021-02-05T19:38:35+00:00 https://www.jneurosci.org/content/41/5/1019 cshalizi to:NB distributed_systems neural_data_analysis neural_coding_and_decoding sparsity lasso to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bc3cdfc5f1e7/ [2101.03093] Learning non-Gaussian graphical models via Hessian scores and triangular transport 2021-01-11T16:32:41+00:00 https://arxiv.org/abs/2101.03093 cshalizi to:NB graphical_models sparsity statistics information_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fb9eca8344a8/ [2101.02776] The Nonconvex Geometry of Linear Inverse Problems 2021-01-11T16:31:53+00:00 https://arxiv.org/abs/2101.02776 cshalizi to:NB inverse_problems sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c45d1367d99b/ [2012.04171] Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization 2021-01-03T19:48:45+00:00 https://arxiv.org/abs/2012.04171 cshalizi to:NB variable_selection sparsity factor_analysis additive_models statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c88603e68cdb/ [2002.02250] Uncovering differential equations from data with hidden variables 2020-12-26T17:46:56+00:00 https://arxiv.org/abs/2002.02250 cshalizi equations_of_motion_from_a_time_series sparsity linear_regression dynamical_systems inference_to_latent_objects in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3ba9d3e1c481/ Baker , Tang , Allen : Feature selection for data integration with mixed multiview data 2020-12-19T16:42:14+00:00 https://projecteuclid.org/euclid.aoas/1608346892 cshalizi to:NB variable_selection lasso sparsity statistics allen.genevera_i. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c18ec82da65c/ [2005.14057] Machine Learning Time Series Regressions with an Application to Nowcasting 2020-12-15T12:59:51+00:00 https://arxiv.org/abs/2005.14057 cshalizi to:NB time_series lasso sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6bfda85c2bca/ [2012.06391] Learning physically consistent mathematical models from data using group sparsity 2020-12-15T01:36:26+00:00 https://arxiv.org/abs/2012.06391 cshalizi to:NB dynamical_systems statistical_inference_for_stochastic_processes sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7760c0b795d9/ [2012.04556] Finding nonlinear system equations and complex network structures from data: a sparse optimization approach 2020-12-12T03:25:09+00:00 https://arxiv.org/abs/2012.04556 cshalizi to:NB dynamical_systems time_series sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2a830c8c26f9/ [2011.12215] Searching for Interactions: Why the Laplace Kernel is your Friend 2020-11-25T14:25:54+00:00 https://arxiv.org/abs/2011.12215 cshalizi to:NB sparsity nonparametrics statistics kernel_methods https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2c6e8e00596e/ [2011.04018] Online Sparse Reinforcement Learning 2020-11-23T17:45:22+00:00 https://arxiv.org/abs/2011.04018 cshalizi to:NB sparsity reinforcement_learning learning_theory https://pinboard.in/ https://pinboard.in/u:cshalizi/b:da676e4c2ce4/ A Survey of Tuning Parameter Selection for High-Dimensional Regression | Annual Review of Statistics and Its Application 2020-11-19T20:05:48+00:00 https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-030718-105038 cshalizi to:NB regression sparsity high-dimensional_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f1362e8d5eb2/ [2004.05387] Vintage Factor Analysis with Varimax Performs Statistical Inference 2020-04-17T15:52:39+00:00 https://arxiv.org/abs/2004.05387 cshalizi factor_analysis sparsity statistics rohe.karl re:g_paper have_read i_remain_unconvinced in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:018615c13937/ [1603.07632] Statistical inference in sparse high-dimensional additive models 2019-10-22T13:49:54+00:00 https://arxiv.org/abs/1603.07632 cshalizi additive_models statistics regression nonparametrics sparsity in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:254865861d99/ [1905.13657] Approximate Cross-Validation in High Dimensions with Guarantees 2019-10-22T13:19:50+00:00 https://arxiv.org/abs/1905.13657 cshalizi to:NB cross-validation sparsity high-dimensional_statistics computational_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6d0b824228ec/ [1909.13189] Learning Sparse Nonparametric DAGs 2019-10-01T16:16:54+00:00 https://arxiv.org/abs/1909.13189 cshalizi causal_discovery graphical_models optimization statistics ravikumar.pradeep xing.eric sparsity to_read in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e6bdf1913768/ Testing Sparsity-Inducing Penalties: Journal of Computational and Graphical Statistics: Vol 0, No 0 2019-08-20T16:07:38+00:00 https://amstat.tandfonline.com/doi/full/10.1080/10618600.2019.1637749 cshalizi to:NB model_checking sparsity regression hypothesis_testing bayesianism re:phil-of-bayes_paper hoff.peter to_besh https://pinboard.in/ https://pinboard.in/u:cshalizi/b:aaba8d8a838f/ High-Dimensional Adaptive Minimax Sparse Estimation With Interactions - IEEE Journals & Magazine 2019-08-20T15:51:54+00:00 https://ieeexplore.ieee.org/document/8700269 cshalizi to:NB statistics high-dimensional_statistics regression sparsity variable_selection linear_regression https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e3bf750aafd7/ [1806.03120] Variational inference for sparse network reconstruction from count data 2019-05-16T20:14:11+00:00 https://arxiv.org/abs/1806.03120 cshalizi to:NB sparsity graphical_models statistics re:6dfb https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3adc36cf07f2/ [1903.04641] Generalized Sparse Additive Models 2019-04-11T00:30:41+00:00 https://arxiv.org/abs/1903.04641 cshalizi to:NB sparsity regression additive_models high-dimensional_statistics statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:b6127a6a59e0/ [1712.05630] Sparse principal component analysis via random projections 2018-09-13T16:40:16+00:00 https://arxiv.org/abs/1712.05630 cshalizi to:NB principal_components sparsity random_projections statistics samworth.richard_j. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:6c614249e1dd/ Large numbers of explanatory variables, a semi-descriptive analysis 2017-08-08T17:59:58+00:00 http://www.pnas.org/content/114/32/8592.abstract.html?etoc cshalizi to:NB statistics regression sparsity lasso high-dimensional_statistics cox.d.r. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:f64e83ba1977/ Oracle M-Estimation for Time Series Models - Giurcanu - 2016 - Journal of Time Series Analysis - Wiley Online Library 2017-04-04T13:16:54+00:00 http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12221/abstract cshalizi bootstrap time_series statistics estimation in_NB sparsity variable_selection high-dimensional_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:7728d02c1d9a/ [1311.5768] An RKHS Approach to Estimation with Sparsity Constraints 2016-12-04T21:30:35+00:00 https://arxiv.org/abs/1311.5768 cshalizi to:NB sparsity compressed_sensing hilbert_space estimation statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:bdb13f5deb4c/ [1209.1508] Confidence sets in sparse regression 2016-11-30T02:04:08+00:00 https://arxiv.org/abs/1209.1508 cshalizi to:NB confidence_sets regression high-dimensional_statistics linear_regression statistics sparsity van_de_geer.sara nickl.richard https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fa957ddc0986/ Estimation and Testing Under Sparsity | Sara van de Geer | Springer 2016-07-06T13:53:56+00:00 http://www.springer.com/us/book/9783319327730 cshalizi to:NB books:noted statistics sparsity high-dimensional_statistics lasso hypothesis_testing confidence_sets van_de_geer.sara to_read empirical_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a21d87b7abc5/ Cat Basis Pursuit 2016-02-24T20:40:33+00:00 http://www.oneweirdkerneltrick.com/catbasis.pdf cshalizi machine_learning cats funny:geeky principal_components sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:031d454cc51b/ [1602.00355] A Spectral Series Approach to High-Dimensional Nonparametric Regression 2016-02-06T19:50:57+00:00 http://arxiv.org/abs/1602.00355 cshalizi to:NB have_read statistics regression nonparametrics sparsity kernel_methods kith_and_kin lee.ann_b. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d6f28b287ea4/ An Introduction to Sparse Stochastic Processes | Communications and Signal Processing | Cambridge University Press 2015-12-17T14:11:44+00:00 http://cambridge.org/9781107058545 cshalizi to:NB books:noted sparsity stochastic_processes compressed_sensing splines statistics levy_processes https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ad6052f5838a/ [1507.05185] Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees 2015-08-05T17:53:26+00:00 http://arxiv.org/abs/1507.05185 cshalizi to:NB regression random_projections computational_statistics statistics sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c444206315c9/ [1507.00280] Network Lasso: Clustering and Optimization in Large Graphs 2015-08-05T14:46:20+00:00 http://arxiv.org/abs/1507.00280 cshalizi to:NB optimization sparsity prediction regression networks https://pinboard.in/ https://pinboard.in/u:cshalizi/b:8850e926060c/ [1506.03850] Generalized Additive Model Selection 2015-07-14T09:55:10+00:00 http://arxiv.org/abs/1506.03850 cshalizi to:NB statistics sparsity additive_models regression kith_and_kin chouldechova.alexandra hastie.trevor https://pinboard.in/ https://pinboard.in/u:cshalizi/b:5d40f2b72122/ How a well-adapted immune system is organized 2015-05-18T01:18:42+00:00 http://www.pnas.org/content/112/19/5950.abstract.html cshalizi to:NB immunology distributed_systems adaptive_behavior sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1a79e6bd52cf/ [1405.5103] Estimation in high dimensions: a geometric perspective 2014-06-11T20:28:30+00:00 http://arxiv.org/abs/1405.5103 cshalizi to:NB statistics high-dimensional_statistics estimation sparsity convexity geometry compressed_sensing to_read https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ff1e079dc4ac/ Information-Theoretic Characterization of Sparse Recovery | AISTATS 2014 | JMLR W&CP 2014-04-20T17:55:03+00:00 http://jmlr.org/proceedings/papers/v33/aksoylar14.html cshalizi to:NB to_read information_theory statistics learning_theory sparsity compressed_sensing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2a48b09609b3/ <span>Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression</span> | AISTATS 2014 | JMLR W&CP 2014-04-15T12:27:29+00:00 http://jmlr.org/proceedings/papers/v33/vats14a.html cshalizi to:NB to_read regression sparsity high-dimensional_statistics statistics vats.divyanshu https://pinboard.in/ https://pinboard.in/u:cshalizi/b:3b3fc0182134/ IEEE Xplore Abstract - Minimum Complexity Pursuit for Universal Compressed Sensing 2014-04-02T01:53:18+00:00 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6719502 cshalizi compressed_sensing sparsity information_theory algorithmic_information_theory statistics in_NB color_me_skeptical https://pinboard.in/ https://pinboard.in/u:cshalizi/b:73d6beaa7dd5/ [1403.7023] Worst possible sub-directions in high-dimensional models 2014-04-01T21:19:01+00:00 http://arxiv.org/abs/1403.7023 cshalizi to:NB high-dimensional_statistics lasso sparsity variable_selection statistics van_de_geer.sara https://pinboard.in/ https://pinboard.in/u:cshalizi/b:d88ae59edb90/ Introduction to Compressed Sensing 2014-03-20T13:21:46+00:00 http://statweb.stanford.edu/~markad/publications/ddek-chapter1-2011.pdf cshalizi to:NB compressed_sensing sparsity estimation statistics linear_algebra re:network_differences entableted https://pinboard.in/ https://pinboard.in/u:cshalizi/b:a18d78f2adc6/ Link Prediction in Graphs with Autoregressive Features 2014-03-11T17:40:17+00:00 http://jmlr.org/papers/v15/richard14a.html cshalizi to:NB time_series network_data_analysis statistics sparsity low-rank_approximation https://pinboard.in/ https://pinboard.in/u:cshalizi/b:9d4df08b858b/ [1402.7349] Learning Graphical Models With Hubs 2014-03-08T22:04:25+00:00 http://arxiv.org/abs/1402.7349 cshalizi to:NB graphical_models statistics sparsity network_data_analysis re:6dfb https://pinboard.in/ https://pinboard.in/u:cshalizi/b:20460cffdec4/ Nickl , van de Geer : Confidence sets in sparse regression 2014-02-20T22:22:07+00:00 http://projecteuclid.org/euclid.aos/1387313392 cshalizi high-dimensional_statistics sparsity confidence_sets regression statistics van_de_geer.sara nickl.richard lasso model_selection linear_regression in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:de2a3bc8882a/ Vu , Lei : Minimax sparse principal subspace estimation in high dimensions 2014-02-20T22:20:20+00:00 http://projecteuclid.org/euclid.aos/1388545673 cshalizi to:NB principal_components sparsity dimension_reduction kith_and_kin vu.vincent statistics to_read minimax high-dimensional_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:ed0ddaddd49e/ [1205.0953] Non-negative least squares for high-dimensional linear models: consistency and sparse recovery without regularization 2014-02-13T18:23:16+00:00 http://arxiv.org/abs/1205.0953 cshalizi to:NB regression high-dimensional_statistics sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2afa11779b41/ Annu. Rev. Neurosci. 2012. 35:485–508 First published online as a Review in Advance on April 5, 2012 The Annual Review of Neuroscience is online at neuro.annualreviews.org This article’s doi: 10.1146/annurev-neuro-062111–150410 Copyright ⃝c 2012 b 2014-02-03T21:42:47+00:00 http://ganguli-gang.stanford.edu/pdf/12.CompSense.pdf cshalizi to:NB high-dimensional_statistics neural_data_analysis neuroscience compressed_sensing sparsity https://pinboard.in/ https://pinboard.in/u:cshalizi/b:0721ee839422/ [1401.6978] Sparsistency and Agnostic Inference in Sparse PCA 2014-02-03T20:25:20+00:00 http://arxiv.org/abs/1401.6978 cshalizi to:NB principal_components sparsity dimension_reduction kith_and_kin statistics vu.vincent lei.jing https://pinboard.in/ https://pinboard.in/u:cshalizi/b:2a94c1eec2f6/ [1312.1706] Swapping Variables for High-Dimensional Sparse Regression from Correlated Measurements 2014-01-02T18:27:15+00:00 http://arxiv.org/abs/1312.1706 cshalizi to:NB high-dimensional_statistics lasso sparsity variable_selection statistics vats.divyanshu https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c1912ea2ab6c/ [1311.6238] Exact inference after model selection via the Lasso 2013-11-26T13:56:29+00:00 http://arxiv.org/abs/1311.6238 cshalizi model_selection confidence_sets sparsity lasso hypothesis_testing regression statistics in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:c32f98a9792e/ [1311.6425] Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching 2013-11-26T04:06:22+00:00 http://arxiv.org/abs/1311.6425 cshalizi to_read network_data_analysis optimization sparsity re:network_differences entableted in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:fa20cf1d019d/ [1311.4175] Estimation in High-dimensional Vector Autoregressive Models 2013-11-21T17:41:27+00:00 http://arxiv.org/abs/1311.4175 cshalizi time_series sparsity statistics re:your_favorite_dsge_sucks in_NB https://pinboard.in/ https://pinboard.in/u:cshalizi/b:00527dc690c7/ Taylor & Francis Online :: Asymptotic Equivalence of Regularization Methods in Thresholded Parameter Space - Journal of the American Statistical Association - Volume 108, Issue 503 2013-09-30T17:45:15+00:00 http://www.tandfonline.com/doi/abs/10.1080/01621459.2013.803972#.Ukmy-hbPUlM cshalizi to:NB lasso sparsity high-dimensional_statistics regression statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:11a674948a6d/ [1309.6702] Statistical paleoclimate reconstructions via Markov random fields 2013-09-27T16:45:27+00:00 http://arxiv.org/abs/1309.6702 cshalizi to:NB climatology variance_estimation random_fields sparsity statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:77aa4d790174/ [1308.2408] Group Lasso for generalized linear models in high dimension 2013-09-17T20:30:01+00:00 http://arxiv.org/abs/1308.2408 cshalizi to:NB linear_regression regression sparsity statistics high-dimensional_statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1d3e66a2dbc3/ [1309.2895] Sparse and Functional Principal Components Analysis 2013-09-12T20:05:36+00:00 http://arxiv.org/abs/1309.2895 cshalizi to:NB sparsity functional_data_analysis principal_components statistics dimension_reduction allen.genevera_i. https://pinboard.in/ https://pinboard.in/u:cshalizi/b:def8a3768d6a/ Nonparametric Sparsity and Regularization 2013-09-05T00:01:07+00:00 http://jmlr.org/papers/v14/rosasco13a.html cshalizi to:NB sparsity hilbert_space regression statistics https://pinboard.in/ https://pinboard.in/u:cshalizi/b:e7686e47d284/ The Steep Price of Sparsity « Normal Deviate 2013-07-29T19:52:06+00:00 http://normaldeviate.wordpress.com/2013/07/27/the-steep-price-of-sparsity/ cshalizimodel_selection track_down_references statistics sparsity variable_selection https://pinboard.in/ https://pinboard.in/u:cshalizi/b:1185172426ca/