Pilanci, Mert

47 publications

ICML 2025 Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes Erica Zhang, Fangzhao Zhang, Mert Pilanci

ICLR 2025 Exploring the Loss Landscape of Regularized Neural Networks via Convex Duality Sungyoon Kim, Aaron Mishkin, Mert Pilanci

ICML 2025 Geometric Algebra Planes: Convex Implicit Neural Volumes Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein, Mert Pilanci

ICLR 2025 Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing Elad Romanov, Fangzhao Zhang, Mert Pilanci

NeurIPS 2024 Adaptive Sampling for Efficient SoftMax Approximation Tavor Z. Baharav, Ryan Kang, Colin Sullivan, Mo Tiwari, Eric Luxenberg, David Tse, Mert Pilanci

NeurIPS 2024 CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks Miria Feng, Zachary Frangella, Mert Pilanci

NeurIPS 2024 Compressing Large Language Models Using Low Rank and Low Precision Decomposition Rajarshi Saha, Naomi Sagan, Varun Srivastava, Andrea J. Goldsmith, Mert Pilanci

ICML 2024 Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time Sungyoon Kim, Mert Pilanci

TMLR 2024 From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford Algebra and Convexity Mert Pilanci

ICML 2024 Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models Fangzhao Zhang, Mert Pilanci

ICLR 2024 Scaling Convex Neural Networks with Burer-Monteiro Factorization Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci

NeurIPS 2024 Spectral Adapter: Fine-Tuning in Spectral Space Fangzhao Zhang, Mert Pilanci

NeurIPS 2023 Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs Rajat Vadiraj Dwaraknath, Tolga Ergen, Mert Pilanci

ICLR 2023 Globally Optimal Training of Neural Networks with Threshold Activation Functions Tolga Ergen, Halil Ibrahim Gulluk, Jonathan Lacotte, Mert Pilanci

NeurIPS 2023 Matrix Compression via Randomized Low Rank and Low Precision Factorization Rajarshi Saha, Varun Srivastava, Mert Pilanci

ICML 2023 Optimal Sets and Solution Paths of ReLU Networks Aaron Mishkin, Mert Pilanci

ICML 2023 Optimal Shrinkage for Distributed Second-Order Optimization Fangzhao Zhang, Mert Pilanci

ICLR 2023 Parallel Deep Neural Networks Have Zero Duality Gap Yifei Wang, Tolga Ergen, Mert Pilanci

NeurIPS 2023 Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks Tolga Ergen, Mert Pilanci

AISTATS 2022 Approximate Function Evaluation via Multi-Armed Bandits Tavor Z. Baharav, Gary Cheng, Mert Pilanci, David Tse

ICLR 2022 Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization Tolga Ergen, Arda Sahiner, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci

ICML 2022 Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions Aaron Mishkin, Arda Sahiner, Mert Pilanci

ICLR 2022 Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John M. Pauly, Morteza Mardani, Mert Pilanci

ICML 2022 Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time Burak Bartan, Mert Pilanci

ICLR 2022 The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program Yifei Wang, Mert Pilanci

ICLR 2022 The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: An Exact Characterization of Optimal Solutions Yifei Wang, Jonathan Lacotte, Mert Pilanci

NeurIPSW 2022 The Solution Path of the Group Lasso Aaron Mishkin, Mert Pilanci

ICML 2022 Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers Arda Sahiner, Tolga Ergen, Batu Ozturkler, John Pauly, Morteza Mardani, Mert Pilanci

ICML 2021 Adaptive Newton Sketch: Linear-Time Optimization with Quadratic Convergence and Effective Hessian Dimensionality Jonathan Lacotte, Yifei Wang, Mert Pilanci

JMLR 2021 Convex Geometry and Duality of Over-Parameterized Neural Networks Tolga Ergen, Mert Pilanci

ICLR 2021 Convex Regularization Behind Neural Reconstruction Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M. Pauly

ICML 2021 Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs Tolga Ergen, Mert Pilanci

NeurIPSW 2021 Greedy Learning for Large-Scale Neural MRI Reconstruction Batu Ozturkler, Arda Sahiner, Tolga Ergen, Arjun D Desai, John M. Pauly, Shreyas Vasanawala, Morteza Mardani, Mert Pilanci

ICLR 2021 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time Tolga Ergen, Mert Pilanci

NeurIPS 2021 Newton-LESS: Sparsification Without Trade-Offs for the Sketched Newton Update Michal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney

ICML 2021 Revealing the Structure of Deep Neural Networks via Convex Duality Tolga Ergen, Mert Pilanci

ICML 2021 Training Quantized Neural Networks to Global Optimality via Semidefinite Programming Burak Bartan, Mert Pilanci

ICLR 2021 Vector-Output ReLU Neural Network Problems Are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-Time Algorithms Arda Sahiner, Tolga Ergen, John M. Pauly, Mert Pilanci

AISTATS 2020 Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models Tolga Ergen, Mert Pilanci

NeurIPS 2020 Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization Michal Derezinski, Burak Bartan, Mert Pilanci, Michael W. Mahoney

NeurIPS 2020 Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization Jonathan Lacotte, Mert Pilanci

ICML 2020 Neural Networks Are Convex Regularizers: Exact Polynomial-Time Convex Optimization Formulations for Two-Layer Networks Mert Pilanci, Tolga Ergen

NeurIPS 2020 Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform Jonathan Lacotte, Sifan Liu, Edgar Dobriban, Mert Pilanci

ICML 2020 Optimal Randomized First-Order Methods for Least-Squares Problems Jonathan Lacotte, Mert Pilanci

NeurIPS 2019 High-Dimensional Optimization in Adaptive Random Subspaces Jonathan Lacotte, Mert Pilanci, Marco Pavone

JMLR 2016 Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares Mert Pilanci, Martin J. Wainwright

NeurIPS 2012 Recovery of Sparse Probability Measures via Convex Programming Mert Pilanci, Laurent E. Ghaoui, Venkat Chandrasekaran