Kaggle forecasting competitions: An overlooked learning opportunity

16 September 2020

Papers citing "Kaggle forecasting competitions: An overlooked learning opportunity"

46 / 46 papers shown

Title
Optimizing AI-Assisted Code Generation Simon Torka Sahin Albayrak 70 0 0 14 Dec 2024
A Benchmark Time Series Dataset for Semiconductor Fabrication Manufacturing Constructed using Component-based Discrete-Event Simulation Models Vamsi Krishna Pendyala H. Sarjoughian Bala Potineni E. Yellig 28 0 0 17 Aug 2024
AnnotatedTables: A Large Tabular Dataset with Language Model Annotations Yaojie Hu Ilias Fountalis Jin Tian N. Vasiloglou LMTD 34 3 0 24 Jun 2024
Beyond Trend Following: Deep Learning for Market Trend Prediction Fernando Berzal Alberto Garcia 40 0 0 10 Jun 2024
Optimizing Sales Forecasts through Automated Integration of Market Indicators Lina Döring Felix Grumbach Pascal Reusch 13 0 0 15 May 2024
Efficient adjustment for complex covariates: Gaining efficiency with DOPE Alexander Mangulad Christgau Niels Richard Hansen 45 2 0 20 Feb 2024
Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques Diyi Liu Hyeonsup Lim M. Uddin Yuandong Liu Lee D. Han Ho-Ling Hwang Shih-Miao Chin 11 0 0 01 Feb 2024
Deep Non-Parametric Time Series Forecaster Syama Sundar Rangapuram Jan Gasthaus Lorenzo Stella Valentin Flunkert David Salinas Yuyang Wang Tim Januschowski AI4TS 25 5 0 22 Dec 2023
Online multiple testing with e-values Ziyu Xu Aaditya Ramdas 26 2 0 10 Nov 2023
Scalable Probabilistic Forecasting in Retail with Gradient Boosted Trees: A Practitioner's Approach Xueying Long Quang Bui G. Oktavian Daniel F. Schmidt Christoph Bergmeir Rakshitha Godahewa Seong Per Lee Kaifeng Zhao Paul Condylis 26 0 0 02 Nov 2023
Efficient Social Choice via NLP and Sampling Lior Ashkenazy Nimrod Talmon 8 0 0 04 Sep 2023
Learning for Interval Prediction of Electricity Demand: A Cluster-based Bootstrapping Approach Rohit Dube Natarajan Gautam Amarnath Banerjee Harsha Nagarajan 11 0 0 04 Sep 2023
Average partial effect estimation using double machine learning Harvey Klyne Rajen Dinesh Shah 14 3 0 17 Aug 2023
Sandwich Boosting for Accurate Estimation in Partially Linear Models for Grouped Data Elliot H. Young Rajen Dinesh Shah 22 1 0 21 Jul 2023
Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge Yvenn Amara-Ouali Y. Goude Nathan Doumèche Pascal Veyret Alexis Thomas ... Aymeric Jan Yannick Deleuze Paul Berhaut Sébastien Treguer Tiphaine Phe-Neau 18 5 0 09 Jun 2023
CyPhERS: A Cyber-Physical Event Reasoning System providing real-time situational awareness for attack and fault response Nils Müller Kaibin Bao Jörg Matthes K. Heussen 33 5 0 26 May 2023
Enhancing Clinical Predictive Modeling through Model Complexity-Driven Class Proportion Tuning for Class Imbalanced Data: An Empirical Study on Opioid Overdose Prediction Yinan Liu Xinyu Dong Weimin Lyu R. Rosenthal Rachel Wong Tengfei Ma Fusheng Wang 30 0 0 09 May 2023
Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management Jonathan Hans Soeseno Sergio González Trista Pei-chun Chen AI4TS 13 1 0 13 Apr 2023
A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation A. Khan Omkar Chaudhari Rohitash Chandra 31 166 0 06 Apr 2023
Variational Boosted Soft Trees Tristan Cinquin Tammo Rukat Philipp Schmidt Martin Wistuba Artur Bekasov BDL UQCV 19 0 0 21 Feb 2023
DivBO: Diversity-aware CASH for Ensemble Learning Yu Shen Yupeng Lu Yang Li Yaofeng Tu Wentao Zhang Bin Cui 17 6 0 07 Feb 2023
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting Ozan Ozyegen Juyoung Wang Mucahit Cevik BDL AI4TS 6 1 0 05 Jan 2023
Contextually Enhanced ES-dRNN with Dynamic Attention for Short-Term Load Forecasting Slawek Smyl Grzegorz Dudek Paweł Pełka AI4TS 29 14 0 18 Dec 2022
SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting Rakshitha Godahewa G. Webb Daniel F. Schmidt Christoph Bergmeir 21 8 0 16 Nov 2022
Experimental study of time series forecasting methods for groundwater level prediction Michael Franklin Mbouopda Thomas Guyet Nicolas Labroche Abel Henriot 21 1 0 28 Sep 2022
Interpretable Time Series Clustering Using Local Explanations Ozan Ozyegen Nicholas Prayogo Mucahit Cevik Ayse Basar FAtt AI4TS 16 1 0 01 Aug 2022
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting Georgia Papacharalampous Hristos Tyralis AI4CE 27 28 0 17 Jun 2022
Lassoed Tree Boosting Alejandro Schuler Yi Li Mark van der Laan 30 3 0 22 May 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 19 22 0 30 Apr 2022
STD: A Seasonal-Trend-Dispersion Decomposition of Time Series Grzegorz Dudek AI4TS 9 32 0 21 Apr 2022
Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practices Hansika Hewamalage Klaus Ackermann Christoph Bergmeir AI4TS 67 87 0 21 Mar 2022
LIMREF: Local Interpretable Model Agnostic Rule-based Explanations for Forecasting, with an Application to Electricity Smart Meter Data Dilini Sewwandi Rajapaksha Christoph Bergmeir AI4TS 14 16 0 15 Feb 2022
LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts Dilini Sewwandi Rajapaksha Christoph Bergmeir Rob J. Hyndman FAtt AI4TS 11 13 0 13 Nov 2021
A Multi-scale Time-series Dataset with Benchmark for Machine Learning in Decarbonized Energy Grids Xiangtian Zheng Nan Xu Loc Trinh Dongqi Wu Tong Huang S. Sivaranjani Yan Liu Le Xie AI4CE 28 43 0 12 Oct 2021
Coresets for Decision Trees of Signals Ibrahim Jubran Ernesto Evgeniy Sanches Shayda I. Newman Dan Feldman 17 17 0 07 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 27 646 0 05 Oct 2021
Fit4CAD: A point cloud benchmark for fitting simple geometric primitives in CAD objects C. Romanengo Andrea Raffo Yifan Qie N. Anwer B. Falcidieno 3DPC 11 22 0 14 May 2021
Monash Time Series Forecasting Archive Rakshitha Godahewa Christoph Bergmeir Geoffrey I. Webb Rob J. Hyndman Pablo Montero-Manso AI4TS 16 144 0 14 May 2021
How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function M. Abolghasemi B. Abbasi Toktam Babaei S. Z. Hosseinifard AI4CE 11 9 0 14 May 2021
A hybrid ensemble method with negative correlation learning for regression Yun Bai Ganglin Tian Yanfei Kang Suling Jia 11 3 0 06 Apr 2021
Exploring the representativeness of the M5 competition data Evangelos Theodorou Shengjie Wang Yanfei Kang Evangelos Spiliotis Spyros Makridakis Vassilios Assimakopoulos 14 16 0 04 Mar 2021
Wielding Occam's razor: Fast and frugal retail forecasting F. Petropoulos Y. Grushka-Cockayne Enno Siemsen Evangelos Spiliotis 17 7 0 23 Feb 2021
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting Longyuan Li Jihai Zhang Junchi Yan Yaohui Jin Yunhao Zhang Yanjie Duan Guangjian Tian AI4TS 21 17 0 31 Jan 2021
Ensembles of Localised Models for Time Series Forecasting Rakshitha Godahewa Kasun Bandara Geoffrey I. Webb Slawek Smyl Christoph Bergmeir AI4TS 27 43 0 30 Dec 2020
Global Models for Time Series Forecasting: A Simulation Study Hansika Hewamalage Christoph Bergmeir Kasun Bandara AI4TS 18 57 0 23 Dec 2020
Forecasting: theory and practice F. Petropoulos D. Apiletti Vassilios Assimakopoulos M. Z. Babai Devon K. Barrow ... J. Arenas Xiaoqian Wang R. L. Winkler Alisa Yusupova F. Ziel AI4TS 36 363 0 04 Dec 2020