Optimization

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication COLT 2024 The LLM Surgeon ICLR 2024 The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis JMLR 2024 The Mamba in the Llama: Distilling and Accelerating Hybrid Models NeurIPS 2024 The Marginal Value of Momentum for Small Learning Rate SGD ICLR 2024 The Non-linear F-Design and Applications to Interactive Learning ICML 2024 The Non-Overlapping Statistical Approximation to Overlapping Group Lasso JMLR 2024 The Nyström method for convex loss functions JMLR 2024 Theoretical and Empirical Analysis of Cost-Function Merging for Implicit Hitting Set WCSP Solving AAAI 2024 Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning NeurIPS 2024 Theoretical Study on Multi-objective Heuristic Search IJCAI 2024 The Power of Extrapolation in Federated Learning NeurIPS 2024 The Price of Adaptivity in Stochastic Convex Optimization COLT 2024 The Price of Implicit Bias in Adversarially Robust Generalization NeurIPS 2024 The Relative Gaussian Mechanism and its Application to Private Gradient Descent AISTATS 2024 The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NeurIPS 2024 The Road Less Scheduled NeurIPS 2024 The Role of n-gram Smoothing in the Age of Neural Networks NAACL 2024 The Sample-Communication Complexity Trade-off in Federated Q-Learning NeurIPS 2024 The sample complexity of ERMs in stochastic convex optimization AISTATS 2024 The Secretary Problem with Predicted Additive Gap NeurIPS 2024 The SMART approach to instance-optimal online learning COLT 2024 The Star Geometry of Critic-Based Regularizer Learning NeurIPS 2024 The Value of Reward Lookahead in Reinforcement Learning NeurIPS 2024 Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024