Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMachine Learning, Volume 113
Volume 113, Number 1, January 2024
- Déborah Sulem
, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong:
Graph similarity learning for change-point detection in dynamic networks. 1-44 - Rahul Singh, Fang Liu, Yin Sun, Ness B. Shroff:
Multi-armed bandits with dependent arms. 45-71 - Vasco Lopes, Fabio Maria Carlucci, Pedro M. Esperança, Marco Singh, Antoine Yang, Victor Gabillon, Hang Xu, Zewei Chen, Jun Wang:
Manas: multi-agent neural architecture search. 73-96 - Ehsan Kazemi, Liqiang Wang:
Efficient zeroth-order proximal stochastic method for nonconvex nonsmooth black-box problems. 97-120 - Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes:
Feature extractor stacking for cross-domain few-shot learning. 121-158 - Dimitris Bertsimas, Kimberly Villalobos Carballo, Léonard Boussioux, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov:
Holistic deep learning. 159-183 - Davide Cacciarelli, Murat Kulahci:
Active learning for data streams: a survey. 185-239 - Young Woong Park, Jinhak Kim, Dan Zhu:
Discordance minimization-based imputation algorithms for missing values in rating data. 241-279 - Nam Le Hai, Trang Nguyen, Ngo Van Linh, Thien Huu Nguyen, Khoat Than:
Continual variational dropout: a view of auxiliary local variables in continual learning. 281-323 - Konstantinos Kalpakis:
Consensus-relevance kNN and covariate shift mitigation. 325-353 - Yanzhe Bekkemoen:
Explainable reinforcement learning (XRL): a systematic literature review and taxonomy. 355-441 - Alex Beeson, Giovanni Montana:
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning. 443-488 - Anna Arutyunova, Anna Großwendt, Heiko Röglin, Melanie Schmidt, Julian Wargalla:
Upper and lower bounds for complete linkage in general metric spaces. 489-518
Volume 113, Number 2, February 2024
- Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant:
A general framework for the practical disintegration of PAC-Bayesian bounds. 519-604 - Cyprien Gilet, Marie Guyomard, Sébastien Destercke, Lionel Fillatre:
Softmin discrete minimax classifier for imbalanced classes and prior probability shifts. 605-645 - Charles A. Hepburn, Giovanni Montana:
Model-based trajectory stitching for improved behavioural cloning and its applications. 647-674 - Mohammadreza Qaraei, Rohit Babbar:
Meta-classifier free negative sampling for extreme multilabel classification. 675-697 - Xingjian Li, Di Hu, Xuhong Li, Haoyi Xiong, Cheng-Zhong Xu, Dejing Dou:
Towards accurate knowledge transfer via target-awareness representation disentanglement. 699-723 - Mike Huisman, Aske Plaat, Jan N. van Rijn:
Subspace Adaptation Prior for Few-Shot Learning. 725-752 - Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike, Xavier Siebert:
Active learning algorithm through the lens of rejection arguments. 753-788 - Cheng-Der Fuh, Chuan-Ju Wang, Chen-Hung Pai:
Markov chain importance sampling for minibatches. 789-814 - Xiaotong Jiang, Xin Zhou, Michael R. Kosorok:
Deep doubly robust outcome weighted learning. 815-842 - John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg, Korbinian Randl:
Automotive fault nowcasting with machine learning and natural language processing. 843-861 - René Heinrich, Christoph Scholz, Stephan Vogt, Malte Lehna:
Targeted adversarial attacks on wind power forecasts. 863-889 - Yuan Zhong, Wei Xu, Xin Gao:
Heterogeneous multi-task feature learning with mixed ℓ 2,1 regularization. 891-932 - Michael Lau, Tamara Schikowski, Holger Schwender:
logicDT: a procedure for identifying response-associated interactions between binary predictors. 933-992 - Vân Anh Huynh-Thu, Pierre Geurts:
Optimizing model-agnostic random subspace ensembles. 993-1042
Volume 113, Number 3, March 2024
- Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi:
Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment. 1043-1067 - Lingfei Ren, Ruimin Hu, Yang Liu, Dengshi Li, Junhang Wu, Yilong Zang, Wenyi Hu:
Improving fraud detection via imbalanced graph structure learning. 1069-1090 - Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Devanshu Shah:
Composition of relational features with an application to explaining black-box predictors. 1091-1132 - Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao:
Differentially private Riemannian optimization. 1133-1161 - Heon Song, Nariaki Mitsuo, Seiichi Uchida, Daiki Suehiro:
No regret sample selection with noisy labels. 1163-1188 - Raoul Heese, Moritz Wolter, Sascha Mücke, Lukas Franken, Nico Piatkowski:
On the effects of biased quantum random numbers on the initialization of artificial neural networks. 1189-1217 - Gayathri Girish, Deepak Mishra, Subrahamanian Moosath K. S.:
Utilising energy function and variational inference training for learning a graph neural network architecture. 1219-1241 - Zezeng Li, Shenghao Li, Lianbao Jin, Na Lei, Zhongxuan Luo:
OT-net: a reusable neural optimal transport solver. 1243-1268 - Thais Luca, Aline Paes, Gerson Zaverucha:
Word embeddings-based transfer learning for boosted relational dependency networks. 1269-1302 - Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli:
Explainable models via compression of tree ensembles. 1303-1328 - Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Structural causal models reveal confounder bias in linear program modelling. 1329-1349 - Victor Verreet, Luc De Raedt, Jessa Bekker:
Modeling PU learning using probabilistic logic programming. 1351-1372 - Zhetong Dong, Hongwei Lin, Chi Zhou, Ben Zhang, Gengchen Li:
Persistence B-spline grids: stable vector representation of persistence diagrams based on data fitting. 1373-1420 - Ioannis Papantonis, Vaishak Belle:
Principled diverse counterfactuals in multilinear models. 1421-1443 - Evangelos Michelioudakis, Alexander Artikis, Georgios Paliouras:
Online semi-supervised learning of composite event rules by combining structure and mass-based predicate similarity. 1445-1481 - Clement Etienam, Kody J. H. Law, Sara Wade, Vitaly Zankin:
Fast deep mixtures of Gaussian process experts. 1483-1508 - Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu:
Correction to: Learning to bid and rank together in recommendation systems. 1509
Volume 113, Number 4, April 2024
- Shudong Zhang, Haichang Gao, Chao Shu, Xiwen Cao, Yunyi Zhou, Jianping He:
Black-box Bayesian adversarial attack with transferable priors. 1511-1528 - Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker:
Hitting the target: stopping active learning at the cost-based optimum. 1529-1547 - Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang:
Partial label learning with emerging new labels. 1549-1565 - Sambhav Jain, Reshma Rastogi:
Parametric non-parallel support vector machines for pattern classification. 1567-1594 - Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao:
Riemannian block SPD coupling manifold and its application to optimal transport. 1595-1622 - Yunyun Wang, Yao Liu, Songcan Chen:
Towards adaptive unknown authentication for universal domain adaptation by classifier paradox. 1623-1641 - Jie-Jing Shao, Xiaowen Yang, Lan-Zhe Guo:
Open-set learning under covariate shift. 1643-1659 - Chen Jia, Yue Zhang:
Meta-learning the invariant representation for domain generalization. 1661-1681 - Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang:
Heterogeneous sets in dimensionality reduction and ensemble learning. 1683-1704 - Xiangyu Yin, Wenjie Ruan, Jonathan E. Fieldsend:
DIMBA: discretely masked black-box attack in single object tracking. 1705-1723 - Tong Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo:
Transfer and share: semi-supervised learning from long-tailed data. 1725-1742 - Tianxiang Qin, Shikui Tu, Lei Xu:
IA-NGM: A bidirectional learning method for neural graph matching with feature fusion. 1743-1769 - Ronghui Mu, Wenjie Ruan, Leandro Soriano Marcolino, Qiang Ni:
3DVerifier: efficient robustness verification for 3D point cloud models. 1771-1798 - Shonosuke Harada, Hisashi Kashima:
InfoCEVAE: treatment effect estimation with hidden confounding variables matching. 1799-1817 - Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao:
Local AdaGrad-type algorithm for stochastic convex-concave optimization. 1819-1838 - Peng Tan, Zhi-Hao Tan, Yuan Jiang, Zhi-Hua Zhou:
Towards enabling learnware to handle heterogeneous feature spaces. 1839-1860 - Lan Li, De-Chuan Zhan, Xin-Chun Li:
Aligning model outputs for class imbalanced non-IID federated learning. 1861-1884 - Guoxi Zhang, Hisashi Kashima:
Learning state importance for preference-based reinforcement learning. 1885-1901 - Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu:
ProtoSimi: label correction for fine-grained visual categorization. 1903-1920 - Suncheng Xiang, Hao Chen, Wei Ran, Zefang Yu, Ting Liu, Dahong Qian, Yuzhuo Fu:
Deep multimodal representation learning for generalizable person re-identification. 1921-1939 - Charles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck, Jan N. van Rijn:
Hyperparameter importance and optimization of quantum neural networks across small datasets. 1941-1966 - Iiro Kumpulainen, Nikolaj Tatti:
Dense subgraphs induced by edge labels. 1967-1987 - Niloofar Ranjbar, Saeedeh Momtazi, MohammadMehdi Homayoonpour:
Explaining recommendation system using counterfactual textual explanations. 1989-2012 - Michela Proietti, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco:
Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening. 2013-2044 - Valentina Arrigoni, Luisa Repele, Dario Marino Saccavino:
Textmatcher: cross-attentional neural network to compare image and text. 2045-2066 - Félix Iglesias Vázquez, Tanja Zseby:
Temporal silhouette: validation of stream clustering robust to concept drift. 2067-2091 - Ruidong Jin, Xin Liu, Tsuyoshi Murata:
Predicting potential real-time donations in YouTube live streaming services via continuous-time dynamic graphs. 2093-2127 - Thanh Duy Do, Thuan Dinh Nguyen, Viet Cuong Ta, Duong Tran Anh, Tuyet-Hanh Tran Thi, Diep Phan, Son T. Mai:
Dynamic weighted ensemble for diarrhoea incidence predictions. 2129-2152 - Elena Battaglia, Federico Peiretti, Ruggero G. Pensa:
Fast parameterless prototype-based co-clustering. 2153-2181 - Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas:
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. 2183-2205 - Manuel Dileo, Matteo Zignani, Sabrina Gaito:
Temporal graph learning for dynamic link prediction with text in online social networks. 2207-2226 - Alberto Berenguer, Jose-Norberto Mazón, David Tomás:
Word embeddings for retrieving tabular data from research publications. 2227-2248 - Bilal Abu-Salih, Mohammed Alweshah, Moutaz Alazab, Manaf Al-Okaily, Muteeb Alahmari, Mohammad Alhabashneh, Saleh Al-Sharaeh:
Natural language inference model for customer advocacy detection in online customer engagement. 2249-2275 - Vidyadhar Jinnappa Aski, Rugved Sanjay Chavan, Vijaypal Singh Dhaka, Geeta Rani, Ester Zumpano, Eugenio Vocaturo:
Forecasting of mobile network traffic and spatio-temporal analysis using modLSTM. 2277-2300
a service of 
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-04-29 21:43 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
