The following pages link to author name string (P43):
Displaying 50 items.
- You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle (Q6318134) (← links)
- 3GPP-inspired Stochastic Geometry-based Mobility Model for a Drone Cellular Network (Q6318146) (← links)
- An Adaptive Remote Stochastic Gradient Method for Training Neural Networks (Q6318195) (← links)
- FSMI: Fast computation of Shannon Mutual Information for information-theoretic mapping (Q6318298) (← links)
- Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning (Q6318383) (← links)
- MAP Inference via L2-Sphere Linear Program Reformulation (Q6318446) (← links)
- Learning Representations for Predicting Future Activities (Q6318470) (← links)
- Efficient and minimal length parametric conformal prediction regions (Q6318483) (← links)
- Stein Point Markov Chain Monte Carlo (Q6318485) (← links)
- Non-cooperative Aerial Base Station Placement via Stochastic Optimization (Q6318516) (← links)
- Mutual Information Scaling and Expressive Power of Sequence Models (Q6318553) (← links)
- Linear Range in Gradient Descent (Q6318591) (← links)
- A New Look at an Old Problem: A Universal Learning Approach to Linear Regression (Q6318606) (← links)
- A Cone-Beam X-Ray CT Data Collection designed for Machine Learning (Q6318617) (← links)
- Physically-interpretable classification of biological network dynamics for complex collective motions (Q6318626) (← links)
- Convolutional neural networks with fractional order gradient method (Q6318674) (← links)
- Stochastic Gradient Coding for Straggler Mitigation in Distributed Learning (Q6318680) (← links)
- Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning (Q6318817) (← links)
- On the Automatic Parameter Selection for Permutation Entropy (Q6318831) (← links)
- Moment-based Estimation of Mixtures of Regression Models (Q6318836) (← links)
- Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables (Q6318878) (← links)
- Randomization of Approximate Bilinear Computation for Matrix Multiplication (Q6318932) (← links)
- Adaptively Truncating Backpropagation Through Time to Control Gradient Bias (Q6318938) (← links)
- Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach (Q6318975) (← links)
- Locally Differentially Private Frequency Estimation with Consistency (Q6319063) (← links)
- Compression with Flows via Local Bits-Back Coding (Q6319088) (← links)
- Distributionally Robust Formulation and Model Selection for the Graphical Lasso (Q6319145) (← links)
- MIST: A Novel Training Strategy for Low-latency Scalable Neural Net Decoders (Q6319147) (← links)
- Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms (Q6319156) (← links)
- Fine-grained Optimization of Deep Neural Networks (Q6319157) (← links)
- Convergence and Margin of Adversarial Training on Separable Data (Q6319178) (← links)
- MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling (Q6319215) (← links)
- Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces (Q6319220) (← links)
- Network Density of States (Q6319254) (← links)
- Efficient Reduction in Shape Parameter Space Dimension for Ship Propeller Blade Design (Q6319261) (← links)
- Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis (Q6319275) (← links)
- On Recurrent Neural Networks for Sequence-based Processing in Communications (Q6319280) (← links)
- Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates (Q6319283) (← links)
- Momentum-Based Variance Reduction in Non-Convex SGD (Q6319287) (← links)
- Optimal nonparametric change point detection and localization (Q6319288) (← links)
- Semi-Parametric Efficient Policy Learning with Continuous Actions (Q6319303) (← links)
- Semi-Supervised Classification on Non-Sparse Graphs Using Low-Rank Graph Convolutional Networks (Q6319315) (← links)
- Nonparametric Bootstrap Inference for the Targeted Highly Adaptive LASSO Estimator (Q6319323) (← links)
- Minimax Rates of Estimating Approximate Differential Privacy (Q6319325) (← links)
- Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension (Q6319330) (← links)
- A Polynomial-Based Approach for Architectural Design and Learning with Deep Neural Networks (Q6319338) (← links)
- Variational Bayes under Model Misspecification (Q6319395) (← links)
- Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback (Q6319405) (← links)
- Graph Filtration Learning (Q6319414) (← links)
- A Rate-Distortion Framework for Explaining Neural Network Decisions (Q6319421) (← links)
