Papers
11,015 papers found
Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters
Qiang Meng, Feng Zhou, Hainan Ren et al.
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi et al.
Improving Non-Autoregressive Translation Models Without Distillation
Xiao Shi Huang, Felipe Perez, Maksims Volkovs
Improving the Accuracy of Learning Example Weights for Imbalance Classification
Yuqi Liu, Bin Cao, Jing Fan
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications
Borja G. León, Murray Shanahan, Francesco Belardinelli
Increasing the Cost of Model Extraction with Calibrated Proof of Work
Adam Dziedzic, Muhammad Ahmad Kaleem, Yu Shen Lu et al.
Incremental False Negative Detection for Contrastive Learning
Tsai-Shien Chen, Wei-Chih Hung, Hung-Yu Tseng et al.
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne et al.
Inductive Relation Prediction Using Analogy Subgraph Embeddings
Jiarui Jin, Yangkun Wang, Kounianhua Du et al.
InfinityGAN: Towards Infinite-Pixel Image Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Yen-Chi Cheng et al.
Information Bottleneck: Exact Analysis of (Quantized) Neural Networks
Stephan Sloth Lorenzen, Christian Igel, Mads Nielsen
Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels
Wentao Zhang, Yexin Wang, Zhenbang You et al.
Information Prioritization through Empowerment in Visual Model-based RL
Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan et al.
Information-theoretic Online Memory Selection for Continual Learning
Shengyang Sun, Daniele Calandriello, Huiyi Hu et al.
Interacting Contour Stochastic Gradient Langevin Dynamics
Wei Deng, Siqi Liang, Botao Hao et al.
Interpretable Unsupervised Diversity Denoising and Artefact Removal
Mangal Prakash, Mauricio Delbracio, Peyman Milanfar et al.
IntSGD: Adaptive Floatless Compression of Stochastic Gradients
Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev et al.
Invariant Causal Representation Learning for Out-of-Distribution Generalization
Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato et al.
Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies
Alex Chan, Alicia Curth, Mihaela van der Schaar
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning
Natalie Dullerud, Karsten Roth, Kimia Hamidieh et al.
Is High Variance Unavoidable in RL? A Case Study in Continuous Control
Johan Bjorck, Carla P Gomes, Kilian Q Weinberger
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma, Xiaorui Liu, Neil Shah et al.
Is Importance Weighting Incompatible with Interpolating Classifiers?
Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque et al.
Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming
Sachin G Konan, Esmaeil Seraj, Matthew Gombolay
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
Wengong Jin, Jeremy Wohlwend, Regina Barzilay et al.