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Gradient Boosting Neural Networks: GrowNet

Gradient Boosting Neural Networks: GrowNet

19 February 2020
Sarkhan Badirli
Xuanqing Liu
Zhengming Xing
Avradeep Bhowmik
Khoa D. Doan
S. Keerthi
    FedML
ArXivPDFHTML

Papers citing "Gradient Boosting Neural Networks: GrowNet"

16 / 16 papers shown
Title
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
Ruxue Shi
Hengrui Gu
Xu Shen
Xin Wang
LMTD
159
0
0
09 May 2025
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems
Si-Yang Liu
Han-Jia Ye
66
5
0
04 Feb 2025
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling
Yury Gorishniy
Akim Kotelnikov
Artem Babenko
LMTD
MoE
89
6
0
31 Oct 2024
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential
  Ordering
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering
A. Habib
Kesheng Wang
Mary-Anne Hartley
Gianfranco Doretto
Donald Adjeroh
LMTD
28
1
0
17 Oct 2024
Forecasting with Hyper-Trees
Forecasting with Hyper-Trees
Alexander März
Kashif Rasul
42
0
0
13 May 2024
Multimodal Clinical Trial Outcome Prediction with Large Language Models
Multimodal Clinical Trial Outcome Prediction with Large Language Models
Wenhao Zheng
Dongsheng Peng
Hongxia Xu
Yun-Qing Li
Hongtu Zhu
Tianfan Fu
Huaxiu Yao
Huaxiu Yao
47
5
0
09 Feb 2024
Boosted Dynamic Neural Networks
Boosted Dynamic Neural Networks
Haichao Yu
Haoxiang Li
G. Hua
Gao Huang
Humphrey Shi
30
7
0
30 Nov 2022
Precision Machine Learning
Precision Machine Learning
Eric J. Michaud
Ziming Liu
Max Tegmark
19
34
0
24 Oct 2022
Towards Domain-Independent Supervised Discourse Parsing Through Gradient
  Boosting
Towards Domain-Independent Supervised Discourse Parsing Through Gradient Boosting
Patrick Huber
Giuseppe Carenini
21
0
0
18 Oct 2022
Revisiting Pretraining Objectives for Tabular Deep Learning
Revisiting Pretraining Objectives for Tabular Deep Learning
Ivan Rubachev
Artem Alekberov
Yu. V. Gorishniy
Artem Babenko
LMTD
21
41
0
07 Jul 2022
Transfer Learning with Deep Tabular Models
Transfer Learning with Deep Tabular Models
Roman Levin
Valeriia Cherepanova
Avi Schwarzschild
Arpit Bansal
C. B. Bruss
Tom Goldstein
A. Wilson
Micah Goldblum
OOD
FedML
LMTD
75
58
0
30 Jun 2022
Transfer learning for ensembles: reducing computation time and keeping
  the diversity
Transfer learning for ensembles: reducing computation time and keeping the diversity
Ilya Shashkov
Nikita Balabin
Evgeny Burnaev
Alexey Zaytsev
8
1
0
27 Jun 2022
On Embeddings for Numerical Features in Tabular Deep Learning
On Embeddings for Numerical Features in Tabular Deep Learning
Yura Gorishniy
Ivan Rubachev
Artem Babenko
LMTD
11
155
0
10 Mar 2022
Revisiting Deep Learning Models for Tabular Data
Revisiting Deep Learning Models for Tabular Data
Yu. V. Gorishniy
Ivan Rubachev
Valentin Khrulkov
Artem Babenko
LMTD
19
696
0
22 Jun 2021
A Generalized Stacking for Implementing Ensembles of Gradient Boosting
  Machines
A Generalized Stacking for Implementing Ensembles of Gradient Boosting Machines
A. Konstantinov
Lev V. Utkin
29
5
0
12 Oct 2020
Time-based Sequence Model for Personalization and Recommendation Systems
Time-based Sequence Model for Personalization and Recommendation Systems
T. Ishkhanov
Maxim Naumov
Xianjie Chen
Yan Zhu
Yuan Zhong
A. Azzolini
Chonglin Sun
Frank Jiang
Andrey Malevich
Liang Xiong
13
16
0
27 Aug 2020
1