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ORCID6th CogMI 2024: Washington, DC, USA
- 6th IEEE International Conference on Cognitive Machine Intelligence, CogMI 2024, Washington, DC, USA, October 28-31, 2024. IEEE 2024, ISBN 979-8-3503-8672-1
- Jingyuan Chou, Jiangzhuo Chen, Madhav V. Marathe:
State-Of-The-Art and Challenges in Causal Inference on Graphs: Confounders and Interferences. 1-13 - Saketh Vishnubhatla, Adrienne Raglin, Raha Moraffah, Huan Liu:
Causal Inductive Biases for Cognitive Machine Learning. 14-16 - Ayron Fears, Adrienne Raglin, Anjon Basak:
Causal Intervention and Semantic Knowledge for Object Relationships. 17-22 - Tomoyoshi Kimura, Ashitabh Misra, Yizhuo Chen, Denizhan Kara, Jinyang Li, Tianshi Wang, Ruijie Wang, Joydeep Bhattacharyya, Jae Kim, Prashant J. Shenoy, Mani Srivastava, Maggie B. Wigness, Tarek F. Abdelzaher:
The Case for Micro Foundation Models to Support Robust Edge Intelligence. 23-31 - Arunava Roy, Dipankar Dasgupta:
Enhancing Federated Learning Security: Combating Clients' Data Poisoning with Classifier Ensembles. 32-39 - James McCoy, Danda B. Rawat:
Optimized Machine Learning Based Multimodal UAV Detection Using Ensemble Stacking. 40-49 - Anjon Basak, Adrienne Raglin:
Using Automated Core and Spurious Features Detection in Scene Recognition to Explain Computer Vision Model. 50-55 - Mostafa Rahgouy, Hamed Babaei Giglou, Mehnaz Tabassum, Dongji Feng, Amit Das, Taher Rahgooy, Gerry V. Dozier, Cheryl D. Seals:
Towards Effective Authorship Attribution: Integrating Class-Incremental Learning. 56-65 - Mrunmayee Dhapre, Jehanzeb Khan, Youngsoo Kim, Thomas Danielson, Shrikant Jadhav:
Automated Framework for Groundwater Monitoring Using DWT with LSTM and Transformers. 66-74 - Jainil Anilkumar Patel
, Mohammadreza Akbari Lor, Shu-Ching Chen, Mei-Ling Shyu, Steven Luis:
Data-Driven Vulnerable Community Identification During Compound Disasters. 75-84 - Abhishek Singh, Charles Lu, Ramesh Raskar:
Overcoming Trust and Incentive Barriers in Decentralized AI. 85-94 - Upendra Sharma, Sriya Ayachitula:
MimicAI: An LLM based system that mimics and explains. 95-102 - Prasanth Sengadu Suresh, Diego Romeres, Prashant Doshi, Siddarth Jain:
Open Human-Robot Collaboration Systems (OHRCS): A Research Perspective. 103-110 - Qingyang Wang, Xuhang Gu, Calton Pu:
A Study of Response Time Instability of Microservices at High Resource Utilization in the Cloud. 111-116 - Thomas Peroutka, Ilir Murturi, Praveen Kumar Donta, Schahram Dustdar:
A Graph-based Approach to Human Activity Recognition. 117-126 - John Frericks, Brandon Kang, Neal Outland, Prashant Doshi, Kyle Johnsen, Aaron Schecter:
Trust and Collaboration Testing in Controlled Human-Robot Environments. 127-136 - Jianyong Xue, Raphaël Lallement, Matteo Morelli:
Sense-making and knowledge construction via constructivist learning paradigm. 137-143 - Logan Cummins, Alexander Sommers, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jabour, Thomas Arnold:
Explainable Anomaly Detection: Counterfactual driven What-If Analysis. 144-151 - Amisha Priyadarshini, Sergio Gago Masagué:
Fair Evaluator: An Adversarial Debiasing-based Deep Learning Framework in Student Admissions. 152-161 - Jinwen Tang, Yi Shang:
Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment. 162-171 - Xian Yeow Lee, Haiyan Wang, Daisuke Katsumata, Takaharu Matsui, Chetan Gupta:
Multi-agent Reinforcement Learning for Dynamic Dispatching in Material Handling Systems. 172-181 - Bsher Karbouj, Per Sören Tobias Schuster, Moritz Blumhagen, Jörg Krüger:
Optimizing Human-Robot Collaboration in Industry 5.0: A Comparative Study of Communication Mediums and Their Impact on Worker Well-being and Productivity. 182-188 - Gawon Lee, Dohee Kim, Segil Park, Sung-Hyun Sim, Ling Liu, Hyerim Bae:
Neural Bezier Interpolation with Manifold Learning for Reliable Vessel Trajectory Prediction. 189-196 - Bohan Jiang, Chengshuai Zhao, Zhen Tan, Huan Liu:
Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models. 197-206 - Jinwen Tang, Qiming Guo, Yunxin Zhao, Yi Shang:
Decoding Linguistic Nuances in Mental Health Text Classification Using Expressive Narrative Stories. 207-216 - Dmitry Bennett, Fernand Gobet:
Cognitive Chunks, Neural Engrams and Natural Concepts: Bridging the Gap between Connectionism and Symbolism. 217-225 - Noman Javed, Dmitry Bennett, Laura K. Bartlett, Peter C. R. Lane, Fernand Gobet:
Evolving Cognitive Models: A Novel Approach to Verbal Learning. 226-233 - Longwei Wang, Aashish Ghimire, KC Santosh:
Enhanced Model Robustness by Integrated Local and Global Processing. 234-239 - Abdullah Bani Melhem, Zain A. Halloush, Ahmed Aleroud:
Dynamic Network Analysis of Cognitive Attacks Using Meta-Network Modeling and Community Detection Algorithms. 240-246 - Surya Majumder, Kushaj Mallick, Wrick Pal, Somenath Chakraborty, Ram Sarkar:
EMDA-Net: Earth Mover's Distance (EMD) influenced Attention-aided Neural Network for Medical Image Classification. 247-256 - Yuliia Lut, Michael Wang, Elissa M. Redmiles, Rachel Cummings:
How We Browse: Measurement and Analysis of Browsing Behavior. 257-264 - Bahadir Eryilmaz, Osman Alperen Koras, Jörg Schlötterer, Christin Seifert:
Investigating the Impact of Randomness on Reproducibility in Computer Vision: A Study on Applications in Civil Engineering and Medicine. 265-274 - Peter C. R. Lane, Fernand Gobet:
Computational Scientific Discovery in Cognitive Science. 275-277 - Hongpeng Jin, Maryam Akhavan Aghdam, Sai Nath Chowdary Medikonduru, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Effective Diversity Optimizations for High Accuracy Deep Ensembles. 278-287 - Jialie Shen, Marie Morrison, Haiyan Miao, Fengshou Gu:
Harnessing Deep Learning for Fault Detection in Industry 4.0: A Multimodal Approach. 288-294
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