diakonikola
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
In this paper, we study the same problem in the Massart noise model that we now define.
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- North America > United States > Wisconsin > Dane County > Madison (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > Afghanistan > Parwan Province > Charikar (0.04)
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
Finding an approximate second-order stationary point (SOSP) is a well-studied and fundamental problem in stochastic nonconvex optimization with many applications in machine learning.
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Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
In fact, without such assumptions, this problem is NP-hard [Sim02; MR18].
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- North America > United States > Wisconsin > Dane County > Madison (0.04)
- North America > United States > Texas > Travis County > Austin (0.04)
Outlier-robustestimationofasparselinearmodel using`1-penalized Huber'sM-estimator
We study the problem of estimating ap-dimensional s-sparse vector in a linear model with Gaussian design and additivenoise.
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- North America > United States > New Jersey > Hudson County > Hoboken (0.04)
- North America > Canada > Quebec > Montreal (0.04)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Testing for Families of Distributions via the Fourier Transform
Alistair Stewart, Ilias Diakonikolas, Clement Canonne
Neural Information Processing Systems http://nips.cc/
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- North America > Canada > Quebec > Montreal (0.04)
- Europe > United Kingdom > England > Oxfordshire > Oxford (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Eric Price, Alistair Stewart
Neural Information Processing Systems http://nips.cc/
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- Asia > Afghanistan > Parwan Province > Charikar (0.04)
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Private Testing of Distributions via Sample Permutations
Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane, Ronitt Rubinfeld
Neural Information Processing Systems http://nips.cc/
- North America > United States > Massachusetts > Middlesex County > Cambridge (0.04)
- North America > United States > Wisconsin > Dane County > Madison (0.04)
- North America > United States > California > San Diego County > San Diego (0.04)
- North America > Canada (0.04)
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart
Neural Information Processing Systems http://nips.cc/
- North America > United States > California > Los Angeles County > Los Angeles (0.28)
- North America > United States > North Carolina > Durham County > Durham (0.04)
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- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.91)
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families
Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant
Neural Information Processing Systems http://nips.cc/
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.14)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
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- (4 more...)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.72)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.72)