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Machine Learning 2. Lecture 6. Learning to Rank

2026LectureКонстантин Вячеславович Воронцов

The learning-to-rank problem: recovering a partial order relation, the pointwise, pairwise and listwise approaches, the linear ranking model, applications; ordinal regression and the ordinal SVM (SVOR); the pairwise criterion, Ranking SVM, RankNet, the transition to the listwise method LambdaRank; ranking search results: query–document objects, assessor ratings, text, link and click features, TF-IDF and its probabilistic meaning, Okapi BM25, PageRank; quality criteria: precision and recall, MAP, the share of defective pairs and its link with AUC, DCG and NDCG, the pFound user behaviour model; the DSSM neural model: a siamese network, word hashing by letter trigrams, training on clicks with negative sampling.
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Machine Learning 2. Adaptive Forecasting Methods

2026LectureКонстантин Вячеславович Воронцов

Time series forecasting problems: the time series model, the forecasting horizon, the least squares method; econometrics as the main source of problems — trends, seasonalities, change points; examples of forecasting sales volumes and electricity prices; the linear autoregression model; a brief survey of forecasting methods; adaptive short-term forecasting methods: the exponential moving average and the smoothing parameter, the models of Holt, Theil–Wage, Winters with linear and exponential trend, adaptive autoregression; the tracking signal and a statistical test of model adequacy, the Trigg–Leach model; adaptive selection and adaptive composition of models, the LAVR method — local adaptation of weights with regularisation, the monotonicity constraint as a regulariser; experiments on the sales forecasting problem.
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Mathematical Analysis 1. Lecture 1

2026LectureСтанислав Шапошников

Naive set theory and Russell's paradox, Kuratowski's ordered pair and the Cartesian product, a function as a subset of a product, composition, injections, surjections and bijections, the group of bijections and the embedding of any group into it, equinumerosity and indicator functions, the Cantor–Bernstein and Cantor theorems.
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290

Geometry. Lecture 2

2026LectureФёдор Попеленский

Finite geometries — the Platonic solids. A reminder — right actions, orbits, stabilisers, fundamental domains (corrected definition) and the example of Z+Z\mathbb{Z} + \mathbb{Z} on the plane; the formula ∣G∣=∣Orb⁡(x)∣⋅∣Stab⁡(x)∣|G| = |\operatorname{Orb}(x)| \cdot |\operatorname{Stab}(x)| and the 48 symmetries of the cube; regular polyhedra — Sosinsky's definition and the definition via flags, a stellated counterexample; the five Platonic solids; regular polytopes in R4\mathbb{R}^4 (six) and in Rn\mathbb{R}^n for n≥5n \ge 5 (the cube, the simplex, the hyperoctahedron) with the coordinates of their vertices; why there are no more than five — face angles and the Schläfli symbol; uniqueness of the gluing and the rigidity theorem; Euler's formula; the finite subgroups of SO(3)SO(3) — Zn\mathbb{Z}_n, DnD_n and the rotation groups of the tetrahedron, cube and icosahedron; the duality cube–octahedron, icosahedron–dodecahedron; which figures on the sphere realise Zn\mathbb{Z}_n, DnD_n and Z2\mathbb{Z}_2.

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