## Stem lasso$ (all stems)

### 29 papers:

- ICML-2015-FercoqGS
- Mind the duality gap: safer rules for the Lasso (OF, AG, JS), pp. 333–342.
- KDD-2015-HallacLB #clustering #graph #network #optimisation #scalability
- Network Lasso: Clustering and Optimization in Large Graphs (DH, JL, SB), pp. 387–396.
- KDD-2015-XuSB #learning #predict
- Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction (TX, JS, JB), pp. 1345–1354.
- KDD-2015-YangSJWDY #learning #visual notation
- Structural Graphical Lasso for Learning Mouse Brain Connectivity (SY, QS, SJ, PW, ID, JY), pp. 1385–1394.
- ICML-c2-2014-LiuZWY
- Safe Screening with Variational Inequalities and Its Application to Lasso (JL, ZZ, JW, JY), pp. 289–297.
- ICML-c2-2014-YanLXH #predict
- Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising (LY, WJL, GRX, DH), pp. 802–810.
- KDD-2014-LiuWY #algorithm #performance
- An efficient algorithm for weak hierarchical lasso (YL, JW, JY), pp. 283–292.
- VMCAI-2014-LeikeT #polynomial #source code #synthesis
- Synthesis for Polynomial Lasso Programs (JL, AT), pp. 434–452.
- ICML-c3-2013-HomrighausenM #persistent
- The lasso, persistence, and cross-validation (DH, DJM), pp. 1031–1039.
- ICML-c3-2013-KalaitzisLLZ
- The Bigraphical Lasso (AAK, JDL, NDL, SZ), pp. 1229–1237.
- ICML-c3-2013-YangX #algorithm #robust
- A Unified Robust Regression Model for Lasso-like Algorithms (WY, HX), pp. 585–593.
- ICML-2012-LozanoS #multi
- Multi-level Lasso for Sparse Multi-task Regression (ACL, GS), p. 80.
- ICML-2012-MairalY #analysis #complexity
- Complexity Analysis of the Lasso Regularization Path (JM, BY), p. 238.
- ICML-2012-VogtR #analysis
- A Complete Analysis of the l_1, p Group-Lasso (JEV, VR), p. 143.
- KDD-2012-ZhouLNY #modelling
- Modeling disease progression via fused sparse group lasso (JZ, JL, VAN, JY), pp. 1095–1103.
- CASE-2011-PampuriSFN #multi
- Multilevel Lasso applied to Virtual Metrology in semiconductor manufacturing (SP, AS, GF, GDN), pp. 244–249.
- ICEIS-v2-2011-JiananDF #summary
- Summary of LASSO and Relative Methods (XJ, SD, XF), pp. 131–134.
- ICML-2011-GhavamzadehLMH #analysis
- Finite-Sample Analysis of Lasso-TD (MG, AL, RM, MWH), pp. 1177–1184.
- LATA-2010-Ehlers #automaton
- Short Witnesses and Accepting Lassos in ω-Automata (RE), pp. 261–272.
- ICML-2010-KimX #multi
- Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity (SK, EPX), pp. 543–550.
- ICML-2010-XuJYKL #kernel #learning #multi #performance
- Simple and Efficient Multiple Kernel Learning by Group Lasso (ZX, RJ, HY, IK, MRL), pp. 1175–1182.
- ICML-2010-YangXKL #learning #online
- Online Learning for Group Lasso (HY, ZX, IK, MRL), pp. 1191–1198.
- KDD-2010-LiuYY #algorithm #performance #problem
- An efficient algorithm for a class of fused lasso problems (JL, LY, JY), pp. 323–332.
- ICML-2009-JacobOV #graph
- Group lasso with overlap and graph lasso (LJ, GO, JPV), pp. 433–440.
- ICML-2009-LiuPZ #coordination #multi #semantics
- Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery (HL, MP, JZ), pp. 649–656.
- ICML-2009-RamanFWDR
- The Bayesian group-Lasso for analyzing contingency tables (SR, TJF, PJW, ED, VR), pp. 881–888.
- ICML-2008-Bach08a #consistency #estimation #named
- Bolasso: model consistent Lasso estimation through the bootstrap (FRB), pp. 33–40.
- ICML-2008-RothF #algorithm #linear #modelling #performance
- The Group-Lasso for generalized linear models: uniqueness of solutions and efficient algorithms (VR, BF), pp. 848–855.
- ICML-2004-KimK #feature model
- Gradient LASSO for feature selection (YK, JK).