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Publication search results
found 122 matches
- 2024
- Kartik Ahuja, Amin Mansouri, Yixin Wang:
Multi-Domain Causal Representation Learning via Weak Distributional Invariances. AISTATS 2024: 865-873 - Narendra Babu Unnam, Krishna Reddy Polepalli, Amit Pandey, Naresh Manwani:
Text Representation Models based on the Spatial Distributional Properties of Word Embeddings. COMAD/CODS 2024: 603-604 - Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, André Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland:
A Distributional Analogue to the Successor Representation. CoRR abs/2402.08530 (2024) - 2023
- Asifa Tassaddiq, Rekha Srivastava, Ruhaila Md. Kasmani, Rabab Alharbi:
Complex Generalized Representation of Gamma Function Leading to the Distributional Solution of a Singular Fractional Integral Equation. Axioms 12(11): 1046 (2023) - Jing Liu, Yang Liu, Wei Zhu, Xiaoguang Zhu, Liang Song:
Distributional and spatial-temporal robust representation learning for transportation activity recognition. Pattern Recognit. 140: 109568 (2023) - Wentai Wu, Ligang He, Weiwei Lin, Carsten Maple:
FedProf: Selective Federated Learning Based on Distributional Representation Profiling. IEEE Trans. Parallel Distributed Syst. 34(6): 1942-1953 (2023) - Melissa Donati, Carlo Strapparava:
A Cognitive Linguistics Analysis of Phrasal Verbs Representation in Distributional Semantics. CLiC-it 2023 - Nilesh Kumar, Ruby Shrestha, Zhiyuan Li, Linwei Wang:
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations. CLIP/FAIMI/EPIMI@MICCAI 2023: 183-193 - Daoxin Li, Kathryn D. Schuler:
Distributional learning of recursive structures: The role of the structural representation. CogSci 2023 - Riccardo Zamboni, Alberto Maria Metelli, Marcello Restelli:
Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning. NeurIPS 2023 - Nilesh Kumar, Ruby Shrestha, Zhiyuan Li, Linwei Wang:
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations. CoRR abs/2308.06434 (2023) - Kartik Ahuja, Amin Mansouri, Yixin Wang:
Multi-Domain Causal Representation Learning via Weak Distributional Invariances. CoRR abs/2310.02854 (2023) - 2022
- Marcos Matabuena, Paulo Félix, Carlos García-Meixide, Francisco Gude:
Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations. Comput. Methods Programs Biomed. 221: 106905 (2022) - Abhik Jana, Siddhant Haldar, Pawan Goyal:
Network embeddings from distributional thesauri for improving static word representations. Expert Syst. Appl. 187: 115868 (2022) - Andrea Bruera, Massimo Poesio:
Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics. Frontiers Artif. Intell. 5: 796793 (2022) - Atefe Pakzad, Morteza Analoui:
A New Approach for Explicit Distributional Semantic Vector Representation Based on Dependency Distance and Bias Elimination. Int. J. Artif. Intell. Tools 31(1): 2250003:1-2250003:25 (2022) - Sergio Muñoz, Carlos Angel Iglesias:
A text classification approach to detect psychological stress combining a lexicon-based feature framework with distributional representations. Inf. Process. Manag. 59(5): 103011 (2022) - Yuanzheng Wang, Xueqi Cheng, Yixing Fan, Xiaofei Zhu, Huasheng Liang, Qiang Yan, Jiafeng Guo:
MGAD: Learning Descriptional Representation Distilled from Distributional Semantics for Unseen Entities. IJCAI 2022: 4404-4410 - Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song:
Learning Fair Representation via Distributional Contrastive Disentanglement. KDD 2022: 1295-1305 - Na Liu, Mark Dras, Wei Emma Zhang:
Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations. RepL4NLP@ACL 2022: 78-90 - Gopalakrishnan Venkatesh, Abhik Jana, Steffen Remus, Özge Sevgili, Gopalakrishnan Srinivasaraghavan, Chris Biemann:
Using distributional thesaurus to enhance transformer-based contextualized representations for low resource languages. SAC 2022: 845-852 - Na Liu, Mark Dras, Wei Emma Zhang:
Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations. CoRR abs/2204.13853 (2022) - Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song:
Learning Fair Representation via Distributional Contrastive Disentanglement. CoRR abs/2206.08743 (2022) - 2021
- Jiating Zhu, Jiannong Cao:
Distributional representation of resting-state fMRI for functional brain connectivity analysis. Neurocomputing 427: 156-168 (2021) - Zihui Zhang, Cuican Yu, Shuang Xu, Huibin Li:
Learning Flexibly Distributional Representation for Low-quality 3D Face Recognition. AAAI 2021: 3465-3473 - Mohamed Aghzal, Asmaa Mourhir:
Distributional Word Representations for Code-mixed Text in Moroccan Darija. ACLING 2021: 266-273 - Hiroki Tanaka, Takeshi Saga, Satoshi Nakamura:
Clustering of Human Movement Trajectories based on Distributional Representations Derived from Bi-directional LSTM Network with Geographical Coordinates. IEEE BigData 2021: 2936-2940 - 2020
- Paulin Melatagia Yonta, Michael Franklin Mbouopda:
Roconnaissance des Entités Nommées En Langues Peu Dotées En Utilisant La Représentation Distributionnelle Multiligue [Named Entity Recognition in Low-resource Languages using Cross-lingual distributional word representation]. ARIMA J. 33: 4 (2020) - Paolo Pedinotti, Alessandro Lenci:
Don't Invite BERT to Drink a Bottle: Modeling the Interpretation of Metonymies Using BERT and Distributional Representations. COLING 2020: 6831-6837 - Zhangyu Wang, Vahid Moosavi:
From PIace2Vec to Multi-Scale Built-Environment Representation: A General-Purpose Distributional Embedding for Urban Data Analysis. LocalRec@SIGSPATIAL 2020: 1:1-1:12
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