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A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time UAI 2025 Differential Privacy Mechanisms in Neural Tangent Kernel Regression WACV 2025 Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees AAAI 2024 Reliable learning in challenging environments NeurIPS 2023 Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models NeurIPS 2023 Fast Provably Robust Decision Trees and Boosting ICML 2022 Provable Guarantees for Understanding Out-of-Distribution Detection AAAI 2022 Sketching based Representations for Robust Image Classification with Provable Guarantees NeurIPS 2022 Adaptive Machine Unlearning NeurIPS 2021 Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees ICML 2021 Towards neural networks that provably know when they don't know ICLR 2020 A Dual Approach to Verify and Train Deep Networks IJCAI 2019 Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance IJCAI 2019 One-shot Coresets: The Case of k-Clustering AISTATS 2018 Reachability Analysis of Deep Neural Networks with Provable Guarantees IJCAI 2018 Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees RSS 2018 Distributed and Provably Good Seedings for k-Means in Constant Rounds ICML 2017 Partitioned Tensor Factorizations for Learning Mixed Membership Models ICML 2017 Efficient Distributed Topic Modeling with Provable Guarantees AISTATS 2014 A Practical Algorithm for Topic Modeling with Provable Guarantees ICML 2013 Efficient Dimensionality Reduction for Canonical Correlation Analysis ICML 2013 Learning Mixtures of Tree Graphical Models NeurIPS 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 Reconstructing Patterns of Information Diffusion from Incomplete Observations NeurIPS 2011