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Post Selection Inference with Kernels
v1v2 (latest)

Post Selection Inference with Kernels

12 October 2016
M. Yamada
Yuta Umezu
Kenji Fukumizu
Ichiro Takeuchi
ArXiv (abs)PDFHTML

Papers citing "Post Selection Inference with Kernels"

15 / 15 papers shown
Title
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
Yanan Li
Fanxu Meng
Muhan Zhang
Shiai Zhu
Shangguang Wang
Mengwei Xu
MoMe
73
0
0
17 May 2025
Neural Networks beyond explainability: Selective inference for sequence
  motifs
Neural Networks beyond explainability: Selective inference for sequence motifs
Antoine Villié
P. Veber
Yohann De Castro
Laurent Jacob
40
0
0
23 Dec 2022
Efficient Aggregated Kernel Tests using Incomplete $U$-statistics
Efficient Aggregated Kernel Tests using Incomplete UUU-statistics
Antonin Schrab
Ilmun Kim
Benjamin Guedj
Arthur Gretton
111
31
0
18 Jun 2022
Valid and Exact Statistical Inference for Multi-dimensional Multiple
  Change-Points by Selective Inference
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference
Ryota Sugiyama
Hiroki Toda
Vo Nguyen Le Duy
Yu Inatsu
Ichiro Takeuchi
39
13
0
18 Oct 2021
Few-shot Learning for Unsupervised Feature Selection
Few-shot Learning for Unsupervised Feature Selection
Atsutoshi Kumagai
Tomoharu Iwata
Yasuhiro Fujiwara
SSL
42
3
0
02 Jul 2021
Conditional Selective Inference for Robust Regression and Outlier
  Detection using Piecewise-Linear Homotopy Continuation
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation
Toshiaki Tsukurimichi
Yu Inatsu
Vo Nguyen Le Duy
Ichiro Takeuchi
84
23
0
22 Apr 2021
Post-selection inference with HSIC-Lasso
Post-selection inference with HSIC-Lasso
Tobias Freidling
B. Poignard
Héctor Climente-González
M. Yamada
66
14
0
29 Oct 2020
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural
  Network Representations Vary with Width and Depth
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen
M. Raghu
Simon Kornblith
OOD
93
283
0
29 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments
GraphITE: Estimating Individual Effects of Graph-structured Treatments
Shonosuke Harada
H. Kashima
CML
97
23
0
29 Sep 2020
Learning Kernel Tests Without Data Splitting
Learning Kernel Tests Without Data Splitting
Jonas M. Kubler
Wittawat Jitkrittum
Bernhard Schölkopf
Krikamol Muandet
65
23
0
03 Jun 2020
FsNet: Feature Selection Network on High-dimensional Biological Data
FsNet: Feature Selection Network on High-dimensional Biological Data
Dinesh Singh
Héctor Climente-González
Mathis Petrovich
Eiryo Kawakami
M. Yamada
89
49
0
23 Jan 2020
More Powerful Selective Kernel Tests for Feature Selection
More Powerful Selective Kernel Tests for Feature Selection
Jen Ning Lim
M. Yamada
Wittawat Jitkrittum
Y. Terada
S. Matsui
Hidetoshi Shimodaira
71
9
0
14 Oct 2019
Gaussian Processes and Kernel Methods: A Review on Connections and
  Equivalences
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
Motonobu Kanagawa
Philipp Hennig
Dino Sejdinovic
Bharath K. Sriperumbudur
GPBDL
151
344
0
06 Jul 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means
M. Lerasle
Z. Szabó
Gaspar Massiot
Guillaume Lecué
208
36
0
13 Feb 2018
Characteristic and Universal Tensor Product Kernels
Characteristic and Universal Tensor Product Kernels
Z. Szabó
Bharath K. Sriperumbudur
179
72
0
28 Aug 2017
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