Papers
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach
Tri Nguyen, Shahana Ibrahim, Xiao Fu
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
Pierre-Alexandre Kamienny, Guillaume Lample, Sylvain Lamprier et al.
Deep Graph Representation Learning and Optimization for Influence Maximization
Chen Ling, Junji Jiang, Junxiang Wang et al.
Deep Laplacian-based Options for Temporally-Extended Exploration
Martin Klissarov, Marlos C. Machado
Deep Latent State Space Models for Time-Series Generation
Linqi Zhou, Michael Poli, Winnie Xu et al.
Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations
Zifan Song, Xiao Gong, Guosheng Hu et al.
Deep Regression Unlearning
Ayush Kumar Tarun, Vikram Singh Chundawat, Murari Mandal et al.
Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery
Dingrong Wang, Deep Shankar Pandey, Krishna Prasad Neupane et al.
Defects of Convolutional Decoder Networks in Frequency Representation
Ling Tang, Wen Shen, Zhanpeng Zhou et al.
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time
Zichang Liu, Jue Wang, Tri Dao et al.
Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback
Tal Lancewicki, Aviv Rosenberg, Dmitry Sotnikov
Delay-agnostic Asynchronous Coordinate Update Algorithm
Xuyang Wu, Changxin Liu, Sindri Magnússon et al.
Delayed Bandits: When Do Intermediate Observations Help?
Emmanuel Esposito, Saeed Masoudian, Hao Qiu et al.
Delayed Feedback in Kernel Bandits
Sattar Vakili, Danyal Ahmed, Alberto Bernacchia et al.
Delving into Noisy Label Detection with Clean Data
Chenglin Yu, Xinsong Ma, Weiwei Liu
Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
Jigang Kim, Daesol Cho, H. Jin Kim
Demystifying Disagreement-on-the-Line in High Dimensions
Donghwan Lee, Behrad Moniri, Xinmeng Huang et al.
Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks
He Zhang, Bang Wu, Shuo Wang et al.
Denoising MCMC for Accelerating Diffusion-Based Generative Models
Beomsu Kim, Jong Chul Ye
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Liangbin Xie, Xintao Wang, Xiangyu Chen et al.
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Eric Mitchell, Yoonho Lee, Alexander Khazatsky et al.
Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score
Shuhai Zhang, Feng Liu, Jiahao Yang et al.
Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions
Ezgi Korkmaz, Jonah Brown-Cohen
Detecting Out-of-distribution Data through In-distribution Class Prior
Xue Jiang, Feng Liu, Zhen Fang et al.
Deterministic equivalent and error universality of deep random features learning
Dominik Schröder, Hugo Cui, Daniil Dmitriev et al.