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Search results for “LIME”

115 results

IMO 2009

2026Problem sheet

50th International Mathematical Olympiad. Bremen, Germany, 2009.
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340

IMO 2015

2026Problem sheet

56th International Mathematical Olympiad. Thailand, 2015.
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320

IMO 2017

2026Problem sheet

58th International Mathematical Olympiad. Rio de Janeiro, Brazil, 2017.
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290

IMO 2021

2026Problem sheet

62nd International Mathematical Olympiad, 2021.
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330

IMO 2022

2026Problem sheet

63rd International Mathematical Olympiad. Oslo, 2022.
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410

IMO 2024

2026Problem sheet

65th International Mathematical Olympiad, 2024.
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560

A curiosity: “supersmooth” varieties

2026TheorySean Cotner

A rigidity condition on schemes, strictly stronger than smoothness, introduced with examples and a look at where it fails to be geometric — no known application, just a curiosity.
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120

Machine Learning 2. Lecture 1. Deep Neural Networks

2026LectureКонстантин Вячеславович Воронцов

Reminder: the neuron model, the multilayer network, stochastic gradient, momentum, vanishing and exploding gradients, ReLU, dropout, batch normalisation; depth matters more than width; feature generation and end-to-end learning; convolutional neural networks: convolution and pooling layers, the standard CNN scheme, AlexNet and ImageNet, residual networks ResNet and Highway Networks; convolutional networks for speech, texts and games; recurrent neural networks, training by BPTT, long short-term memory networks LSTM, the peephole variant, GRU.
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390

Machine Learning 2. Lecture 2. Neural Networks for Unsupervised Learning

2026LectureКонстантин Вячеславович Воронцов

Kohonen networks: clustering as a two-layer neural network, the hard (WTA) and soft (WTM) competition rules, self-organising Kohonen maps and their interpretation; autoencoders: the formulation of the problem, the linear autoencoder and the principal component method, sparse, denoising, contractive, relational and variational autoencoders, reparametrisation, autoencoders for supervised learning, multilayer autoencoders; joint training of several models: pre-training and transfer learning, multi-task learning and few-shot learning, self-supervised learning, distillation and surrogate modelling, learning using privileged information (LUPI), generative adversarial networks (GAN).
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210