Papers
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
Jerry Yao-Chieh Hu, Weimin Wu, Zhuoru Li et al.
On the Ability of Developers' Training Data Preservation of Learnware
Hao-Yi Lei, Zhi-Hao Tan, Zhi-Hua Zhou
On the Adversarial Robustness of Benjamini Hochberg
Louis L Chen, Roberto Szechtman, Matan Seri
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
Pratiksha Thaker, Amrith Setlur, Zhiwei Steven Wu et al.
On the cohesion and separability of average-link for hierarchical agglomerative clustering
Eduardo S. Laber, Miguel Batista
On the Comparison between Multi-modal and Single-modal Contrastive Learning
Wei Huang, Andi Han, Yongqiang Chen et al.
On the Complexity of Identification in Linear Structural Causal Models
Julian Dörfler, Benito van der Zander, Markus Bläser et al.
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
Nirmit Joshi, Theodor Misiakiewicz, Nathan Srebro
On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
Shubham Bharti, Stephen Wright, Adish Singla et al.
On the Computational Complexity of Private High-dimensional Model Selection
Saptarshi Roy, Zehua Wang, Ambuj Tewari
On the Computational Landscape of Replicable Learning
Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas et al.
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
Daniel Haimovich, Dima Karamshuk, Fridolin Linder et al.
On the Effects of Data Scale on UI Control Agents
Wei Li, William Bishop, Alice Li et al.
On the Efficiency of ERM in Feature Learning
Ayoub El Hanchi, Chris J. Maddison, Murat A. Erdogdu
On the Expressive Power of Tree-Structured Probabilistic Circuits
Lang Yin, Han Zhao
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks
Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen et al.
On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
Yubo Ye, Maryam Toloubidokhti, Sumeet Vadhavkar et al.
On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function
Yu Xiang, Jie Qiao, Zhefeng Liang et al.
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Jiong Zhu, Gaotang Li, Yao-An Yang et al.
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
Guhan Chen, Yicheng Li, Qian Lin
On the Inductive Bias of Stacking Towards Improving Reasoning
Nikunj Saunshi, Stefani Karp, Shankar Krishnan et al.
On the Limitations of Fractal Dimension as a Measure of Generalization
Charlie B. Tan, Inés García-Redondo, Qiquan Wang et al.
On the Necessity of Collaboration for Online Model Selection with Decentralized Data
Junfan Li, Zheshun Wu, Zenglin Xu et al.