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Iti Chaturvedi
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2020 – today
- 2024
- [j18]Iti Chaturvedi, Vlad Pandelea, Erik Cambria, Roy E. Welsch, Bithin Datta:
Barrier Function to Skin Elasticity in Talking Head. Cogn. Comput. 16(6): 3405-3416 (2024) - [j17]Iti Chaturvedi, Ranjan Satapathy, Curtis Lynch, Erik Cambria:
Predicting word vectors for microtext. Expert Syst. J. Knowl. Eng. 41(8) (2024) - 2023
- [j16]Frank Xing, Björn W. Schuller, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Guest Editorial Neurosymbolic AI for Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1711-1715 (2023) - 2022
- [j15]Iti Chaturvedi, Qian Chen, Erik Cambria, Desmond McConnell:
Landmark calibration for facial expressions and fish classification. Signal Image Video Process. 16(2): 377-384 (2022) - [j14]Iti Chaturvedi, Qian Chen, Roy E. Welsch, Kishor Thapa, Erik Cambria:
Gaussian correction for adversarial learning of boundaries. Signal Process. Image Commun. 109: 116841 (2022) - 2021
- [j13]Iti Chaturvedi, Chit Lin Su, Roy E. Welsch:
Fuzzy Aggregated Topology Evolution for Cognitive Multi-tasks. Cogn. Comput. 13(1): 96-107 (2021) - [j12]Iti Chaturvedi, Kishor Thapa, Sandro Cavallari, Erik Cambria, Roy E. Welsch:
Predicting video engagement using heterogeneous DeepWalk. Neurocomputing 465: 228-237 (2021) - [j11]Qian Chen, Iti Chaturvedi, Shaoxiong Ji, Erik Cambria:
Sequential fusion of facial appearance and dynamics for depression recognition. Pattern Recognit. Lett. 150: 115-121 (2021) - 2020
- [j10]Ana Valdivia, Eugenio Martínez-Cámara, Iti Chaturvedi, María Victoria Luzón, Erik Cambria, Yew-Soon Ong, Francisco Herrera:
What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. J. Ambient Intell. Humaniz. Comput. 11(1): 39-52 (2020) - [c20]Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Roy E. Welsch:
Genetic Programming for Domain Adaptation in Product Reviews. CEC 2020: 1-8 - [c19]Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
COAL: Convolutional Online Adaptation Learning for Opinion Mining. ICDM (Workshops) 2020: 15-22 - [c18]Iti Chaturvedi, Jin Xiang:
Constrained Manifold Learning for Videos. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [j9]Ana Valdivia, Emiliya Hrabova, Iti Chaturvedi, María Victoria Luzón, Luigi Troiano, Erik Cambria, Francisco Herrera:
Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods. Neurocomputing 353: 3-16 (2019) - [j8]Iti Chaturvedi, Ranjan Satapathy, Sandro Cavallari, Erik Cambria:
Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognit. Lett. 125: 264-270 (2019) - 2018
- [j7]Iti Chaturvedi, Erik Cambria, Roy E. Welsch, Francisco Herrera:
Distinguishing between facts and opinions for sentiment analysis: Survey and challenges. Inf. Fusion 44: 65-77 (2018) - [j6]Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Bayesian network based extreme learning machine for subjectivity detection. J. Frankl. Inst. 355(4): 1780-1797 (2018) - [c17]Tom Young, Erik Cambria, Iti Chaturvedi, Hao Zhou, Subham Biswas, Minlie Huang:
Augmenting End-to-End Dialogue Systems With Commonsense Knowledge. AAAI 2018: 4970-4977 - [c16]Qian Chen, Edoardo Ragusa, Iti Chaturvedi, Erik Cambria, Rodolfo Zunino:
Text-Image Sentiment Analysis. CICLing (2) 2018: 169-180 - [c15]Qian Chen, Iti Chaturvedi, Soujanya Poria, Erik Cambria, Lorenzo Malandri:
Learning Visual Concepts in Images Using Temporal Convolutional Networks. SSCI 2018: 1280-1284 - [r1]Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Sentiment Analysis, Basic Tasks of. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - 2017
- [j5]Ranjan Satapathy, Iti Chaturvedi, Erik Cambria, Shirley S. Ho, Jin-Cheon Na:
Subjectivity Detection in Nuclear Energy Tweets. Computación y Sistemas 21(4) (2017) - [c14]Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Vincent Wenchen Zheng:
Learning Word Vectors in Deep Walk using Convolution. FLAIRS 2017: 323-328 - [c13]Aparup Khatua, Erik Cambria, Apalak Khatua, Iti Chaturvedi:
Let's Chat about Brexit! A Politically-Sensitive Dialog System Based on Twitter Data. ICDM Workshops 2017: 393-398 - [c12]Ranjan Satapathy, Claudia Guerreiro, Iti Chaturvedi, Erik Cambria:
Phonetic-Based Microtext Normalization for Twitter Sentiment Analysis. ICDM Workshops 2017: 407-413 - [i1]Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Basic tasks of sentiment analysis. CoRR abs/1710.06536 (2017) - 2016
- [j4]Iti Chaturvedi, Yew-Soon Ong, Ivor W. Tsang, Roy E. Welsch, Erik Cambria:
Learning word dependencies in text by means of a deep recurrent belief network. Knowl. Based Syst. 108: 144-154 (2016) - [c11]Soujanya Poria, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis. ICDM 2016: 439-448 - [c10]Iti Chaturvedi, Erik Cambria, Soujanya Poria, Rajiv Bajpai:
Bayesian Deep Convolution Belief Networks for Subjectivity Detection. ICDM Workshops 2016: 916-923 - [c9]Soujanya Poria, Iti Chaturvedi, Erik Cambria, Federica Bisio:
Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis. IJCNN 2016: 4465-4473 - [c8]Iti Chaturvedi, Erik Cambria, David Vilares:
Lyapunov filtering of objectivity for Spanish Sentiment Model. IJCNN 2016: 4474-4481 - 2015
- [j3]Iti Chaturvedi, Yew-Soon Ong, Rajesh Vellore Arumugam:
Deep transfer learning for classification of time-delayed Gaussian networks. Signal Process. 110: 250-262 (2015) - [c7]Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, Iti Chaturvedi:
The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis. CICLing (2) 2015: 3-22 - [c6]Anupam Mondal, Iti Chaturvedi, Dipankar Das, Rajiv Bajpai, Sivaji Bandyopadhyay:
Lexical Resource for Medical Events: A Polarity Based Approach. ICDM Workshops 2015: 1302-1309 - 2013
- [b1]Iti Chaturvedi:
Bayesian framework for building gene regulatory networks including delays. Nanyang Technological University, Singapore, 2013 - 2011
- [c5]Jie Zheng, Iti Chaturvedi, Jagath C. Rajapakse:
Integration of Epigenetic Data in Bayesian Network Modeling of Gene Regulatory Network. PRIB 2011: 87-96 - [c4]Jagath C. Rajapakse, Iti Chaturvedi:
Stability of Inferring Gene Regulatory Structure with Dynamic Bayesian Networks. PRIB 2011: 237-246 - 2010
- [j2]Iti Chaturvedi, Jagath C. Rajapakse:
Building gene networks with time-delayed regulations. Pattern Recognit. Lett. 31(14): 2133-2137 (2010) - [c3]Jagath C. Rajapakse, Iti Chaturvedi:
Gene regulatory networks with variable-order dynamic Bayesian networks. IJCNN 2010: 1-5
2000 – 2009
- 2008
- [c2]Iti Chaturvedi, Jagath C. Rajapakse:
Fusion of Gene Regulatory and Protein Interaction Networks Using Skip-Chain Models. PRIB 2008: 214-224 - 2007
- [c1]Iti Chaturvedi, Meena K. Sakharkar, Jagath C. Rajapakse:
Validation of Gene Regulatory Networks from Protein-Protein Interaction Data: Application to Cell-Cycle Regulation. PRIB 2007: 300-310 - 2005
- [j1]Kishore R. Sakharkar, Iti Chaturvedi, Vincent T. K. Chow, Chee Keong Kwoh, Pandjassarame Kangueane, Meena Kishore Sakharkar:
u-Genome: A Database on Genome Design in Unicellular Genomes. Silico Biol. 5(5-6): 611-615 (2005)
Coauthor Index
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