Papers
Combating Collusion Rings Is Hard but Possible
Niclas Boehmer, Robert Bredereck, André Nichterlein
Combating Sampling Bias: A Self-Training Method in Credit Risk Models
Jingxian Liao, Wei Wang, Jason Xue et al.
Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey
Prajjwal Bhargava, Vincent Ng
Competing for Resources: Estimating Adversary Strategy for Effective Plan Generation
Lukáš Chrpa, Pavel Rytíř, Rostislav Horčík et al.
Competing Mutual Information Constraints with Stochastic Competition-Based Activations for Learning Diversified Representations
Konstantinos P. Panousis, Anastasios Antoniadis, Sotirios Chatzis
Compilation of Aggregates in ASP Systems
Giuseppe Mazzotta, Francesco Ricca, Carmine Dodaro
Complementary Attention Gated Network for Pedestrian Trajectory Prediction
Jinghai Duan, Le Wang, Chengjiang Long et al.
Complexity of Deliberative Coalition Formation
Edith Elkind, Abheek Ghosh, Paul Goldberg
Comprehensive Regularization in a Bi-directional Predictive Network for Video Anomaly Detection
Chengwei Chen, Yuan Xie, Shaohui Lin et al.
Computing Diverse Shortest Paths Efficiently: A Theoretical and Experimental Study
Tesshu Hanaka, Yasuaki Kobayashi, Kazuhiro Kurita et al.
Concentration Network for Reinforcement Learning of Large-Scale Multi-Agent Systems
Qingxu Fu, Tenghai Qiu, Jianqiang Yi et al.
Conditional Abstract Dialectical Frameworks
Jesse Heyninck, Matthias Thimm, Gabriele Kern-Isberner et al.
Conditional Collaborative Filtering Process for Top-K Recommender System (Student Abstract)
Guanyu Wang, Xovee Xu, Ting Zhong et al.
Conditional Generative Model Based Predicate-Aware Query Approximation
Nikhil Sheoran, Subrata Mitra, Vibhor Porwal et al.
Conditional Local Convolution for Spatio-Temporal Meteorological Forecasting
Haitao Lin, Zhangyang Gao, Yongjie Xu et al.
Conditional Loss and Deep Euler Scheme for Time Series Generation
Carl Remlinger, Joseph Mikael, Romuald Elie
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data
Hari Prasanna Das, Ryan Tran, Japjot Singh et al.
Confidence Calibration for Intent Detection via Hyperspherical Space and Rebalanced Accuracy-Uncertainty Loss
Yantao Gong, Cao Liu, Fan Yang et al.
Conjugated Discrete Distributions for Distributional Reinforcement Learning
Björn Lindenberg, Jonas Nordqvist, Karl-Olof Lindahl
Consent as a Foundation for Responsible Autonomy
Munindar P. Singh
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning
Yecheng Jason Ma, Andrew Shen, Osbert Bastani et al.
Consistency Regularization for Adversarial Robustness
Jihoon Tack, Sihyun Yu, Jongheon Jeong et al.
Constrained Prescriptive Trees via Column Generation
Shivaram Subramanian, Wei Sun, Youssef Drissi et al.
Constraint-Driven Explanations for Black-Box ML Models
Aditya A. Shrotri, Nina Narodytska, Alexey Ignatiev et al.
Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning
Tong Mu, Georgios Theocharous, David Arbour et al.