Papers
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration
Gavin Kerrigan, Padhraic Smyth, Mark Steyvers
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
Aryan Deshwal, Jana Doppa
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers
Albert Gu, Isys Johnson, Karan Goel et al.
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe Yu, Aviral Kumar, Rafael Rafailov et al.
Communication-efficient SGD: From Local SGD to One-Shot Averaging
Artin Spiridonoff, Alex Olshevsky, Yannis Paschalidis
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
Rabeeh Karimi Mahabadi, James Henderson, Sebastian Ruder
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization
Haochuan Li, Yi Tian, Jingzhao Zhang et al.
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features
Thomas McDonald, Mauricio Álvarez
Compositional Reinforcement Learning from Logical Specifications
Kishor Jothimurugan, Suguman Bansal, Osbert Bastani et al.
Compositional Transformers for Scene Generation
Dor Arad Hudson, Larry Zitnick
Comprehensive Knowledge Distillation with Causal Intervention
Xiang Deng, Zhongfei Zhang
Compressed Video Contrastive Learning
Yuqi Huo, Mingyu Ding, Haoyu Lu et al.
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition
Lucas Liebenwein, Alaa Maalouf, Dan Feldman et al.
Compressive Visual Representations
Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama et al.
Computer-Aided Design as Language
Yaroslav Ganin, Sergey Bartunov, Yujia Li et al.
Concentration inequalities under sub-Gaussian and sub-exponential conditions
Andreas Maurer, Massimiliano Pontil
Conditional Generation Using Polynomial Expansions
Grigorios Chrysos, Markos Georgopoulos, Yannis Panagakis
Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical Systems
Jiayang Xu, Aniruddhe Pradhan, Karthikeyan Duraisamy
Conditioning Sparse Variational Gaussian Processes for Online Decision-making
Wesley J Maddox, Samuel Stanton, Andrew G Wilson
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhanqiu Zhang, Jie Wang, Jiajun Chen et al.
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality
Songyuan Zhang, ZHANGJIE CAO, Dorsa Sadigh et al.
Confident Anchor-Induced Multi-Source Free Domain Adaptation
Jiahua Dong, Zhen Fang, Anjin Liu et al.
Conflict-Averse Gradient Descent for Multi-task learning
Bo Liu, Xingchao Liu, Xiaojie Jin et al.
Conformal Bayesian Computation
Edwin Fong, Chris C Holmes
Conformal Prediction using Conditional Histograms
Matteo Sesia, Yaniv Romano