Theory

Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021 Scalable Certified Segmentation via Randomized Smoothing ICML 2021 Scalable Verification of Quantized Neural Networks AAAI 2021 Scalars are universal: Equivariant machine learning, structured like classical physics NeurIPS 2021 Scaling Laws for Acoustic Models Interspeech 2021 Scaling Properties of Deep Residual Networks ICML 2021 Searching for Search Errors in Neural Morphological Inflection EACL 2021 Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification NeurIPS 2021 Separation and Concentration in Deep Networks ICLR 2021 Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics NeurIPS 2021 SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation EMNLP 2021 Sequence to General Tree: Knowledge-Guided Geometry Word Problem Solving ACL 2021 SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality COLT 2021 Shape-based Feature Engineering for Solar Flare Prediction AAAI 2021 Shape From Sky: Polarimetric Normal Recovery Under the Sky CVPR 2021 Shapley Residuals: Quantifying the limits of the Shapley value for explanations NeurIPS 2021 Simple Spectral Graph Convolution ICLR 2021 Simpson's Bias in NLP Training AAAI 2021 Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NeurIPS 2021 Softmax Policy Gradient Methods Can Take Exponential Time to Converge COLT 2021 Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent NeurIPS 2021 Some Theoretical Insights into Wasserstein GANs JMLR 2021 Spatio-Temporal Graph Scattering Transform ICLR 2021 Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ NeurIPS 2021 Stability and Generalization for Randomized Coordinate Descent IJCAI 2021