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Bibliografski detalji
Glavni autori:	Verma, Nakul, Kpotufe, Samory, Dasgupta, Sanjoy
Format:	Preprint
Izdano:	2012
Teme:	Machine Learning
Online pristup:	https://arxiv.org/abs/1205.2609
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!

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An Efficient Variant of One-Class SVM with Lifelong Online Learning Guarantees
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Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning
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Distributionally-Constrained Adversaries in Online Learning
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Distribution-Free Rates in Neyman-Pearson Classification
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Transfer Neyman-Pearson Algorithm for Outlier Detection
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Nonlinear Meta-Learning Can Guarantee Faster Rates
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Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products
od: Yuan, Gan, i dr.
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Neyman-Pearson Classification under Both Null and Alternative Distributions Shift
od: Kalan, Mohammadreza M., i dr.
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Convergence Behavior of an Adversarial Weak Supervision Method
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Online Consistency of the Nearest Neighbor Rule
od: Dasgupta, Sanjoy, i dr.
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New bounds on the cohesion of complete-link and other linkage methods for agglomeration clustering
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Learning Smooth Distance Functions via Queries
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Learnability with Partial Labels and Adaptive Nearest Neighbors
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Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
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t-SNE Exaggerates Clusters, Provably
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Low-Precision Streaming PCA
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Graph neural networks extrapolate out-of-distribution for shortest paths
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Deep Autoregressive Models as Causal Inference Engines
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On the Intrinsic Dimensions of Data in Kernel Learning
od: Takhanov, Rustem
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Empowering Decision Trees via Shape Function Branching
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Rethinking Intrinsic Dimension Estimation in Neural Representations
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A Novel Approach for Intrinsic Dimension Estimation
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Measuring the Intrinsic Dimension of Earth Representations
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Measuring Intrinsic Dimension of Token Embeddings
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On Convolutions, Intrinsic Dimension, and Diffusion Models
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Efficient Long-Tail Learning in Latent Space by sampling Synthetic Data
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Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension
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NeurCAM: Interpretable Neural Clustering via Additive Models
od: Upadhya, Nakul, i dr.
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Surrogate Graph Partitioning for Spatial Prediction
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Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension
od: Andriopoulos, George, i dr.
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A Connection Between Score Matching and Local Intrinsic Dimension
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Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation
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eDCF: Estimating Intrinsic Dimension using Local Connectivity
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Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension
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Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension
od: Klivans, Adam R., i dr.
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Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability
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'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning
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A Wiener Process Perspective on Local Intrinsic Dimension Estimation Methods
od: Tempczyk, Piotr, i dr.
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Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces
od: Chowdhury, Sanjoy, i dr.
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