The following pages link to has companion code repository (P1687):
Displaying 50 items.
- Modeling and Optimization Trade-off in Meta-learning (Q6352149) (← links)
- A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks (Q6352187) (← links)
- Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent (Q6352225) (← links)
- Sheet diagrams for bimonoidal categories (Q6352227) (← links)
- Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints (Q6352255) (← links)
- A Sparse Beta Regression Model for Network Analysis (Q6352260) (← links)
- LEAD: Min-Max Optimization from a Physical Perspective (Q6352287) (← links)
- Data-Driven Stabilization of Periodic Orbits (Q6352291) (← links)
- Interior Point Solving for LP-based prediction+optimisation (Q6352297) (← links)
- Dynamic Algorithms for Online Multiple Testing (Q6352300) (← links)
- Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls (Q6352326) (← links)
- The leapfrog algorithm as nonlinear Gauss-Seidel (Q6352330) (← links)
- Physics-Based Deep Learning for Fiber-Optic Communication Systems (Q6352349) (← links)
- On Model Identification and Out-of-Sample Prediction of Principal Component Regression: Applications to Synthetic Controls (Q6352373) (← links)
- Correlation Robust Influence Maximization (Q6352396) (← links)
- Deep Learning for Individual Heterogeneity: An Automatic Inference Framework (Q6352413) (← links)
- Deep Networks from the Principle of Rate Reduction (Q6352427) (← links)
- Parallelizing multiple precision Taylor series method for integrating the Lorenz system (Q6352468) (← links)
- Real-valued Evolutionary Multi-modal Multi-objective Optimization by Hill-Valley Clustering (Q6352469) (← links)
- On Graph Neural Networks versus Graph-Augmented MLPs (Q6352489) (← links)
- Channel Estimation and Equalization for CP-OFDM-based OTFS in Fractional Doppler Channels (Q6352521) (← links)
- Post-selection inference with HSIC-Lasso (Q6352561) (← links)
- Domain adaptation under structural causal models (Q6352580) (← links)
- Quantum advantage for differential equation analysis (Q6352584) (← links)
- $\sigma$-Ridge: group regularized ridge regression via empirical Bayes noise level cross-validation (Q6352590) (← links)
- Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough (Q6352609) (← links)
- A Greedy Algorithm for Quantizing Neural Networks (Q6352610) (← links)
- Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions (Q6352614) (← links)
- Robust Localization in Wireless Networks From Corrupted Signals (Q6352655) (← links)
- General Data Analytics with Applications to Visual Information Analysis: A Provable Backward-Compatible Semisimple Paradigm over T-Algebra (Q6352725) (← links)
- c-lasso -- a Python package for constrained sparse and robust regression and classification (Q6352804) (← links)
- Representations of Energy Landscapes by Sublevelset Persistent Homology: An Example With n-Alkanes (Q6352812) (← links)
- Distributed Machine Learning for Computational Engineering using MPI (Q6352860) (← links)
- Exact Asymptotics for Linear Quadratic Adaptive Control (Q6352864) (← links)
- Multi-Iteration Stochastic Optimizers (Q6352907) (← links)
- AdaDGS: An adaptive black-box optimization method with a nonlocal directional Gaussian smoothing gradient (Q6352953) (← links)
- Federated Knowledge Distillation (Q6352998) (← links)
- SISO RIS-Enabled Joint 3D Downlink Localization and Synchronization (Q6353003) (← links)
- Binary Neural Network Aided CSI Feedback in Massive MIMO System (Q6353042) (← links)
- Efficient Hyperparameter Tuning with Dynamic Accuracy Derivative-Free Optimization (Q6353108) (← links)
- Neural Stochastic Contraction Metrics for Learning-based Control and Estimation (Q6353113) (← links)
- Efficient quantum algorithm for dissipative nonlinear differential equations (Q6353117) (← links)
- Optimal Resource and Demand Redistribution for Healthcare Systems Under Stress from COVID-19 (Q6353170) (← links)
- Pathwise Conditioning of Gaussian Processes (Q6353247) (← links)
- GPU Accelerated Convex Approximations for Fast Multi-Agent Trajectory Optimization (Q6353285) (← links)
- Solving Inverse Problems With Deep Neural Networks -- Robustness Included? (Q6353287) (← links)
- Modeling and Optimizing Resource Allocation Decisions through Multi-model Markov Decision Processes with Capacity Constraints (Q6353306) (← links)
- Exterior-point Optimization for Sparse and Low-rank Optimization (Q6353338) (← links)
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (Q6353342) (← links)
- Approximately Exact Line Search (Q6353358) (← links)
