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It generalizes algorithms such as [[gradient descent]] and [[Multiplicative weight update method|mult ...ticular geometries.<ref>Nemirovski, Arkadi (2012) Tutorial: mirror descent algorithms for large-scale deterministic and stochastic convex optimization.https://ww ...

...Competitive analysis (online algorithm)|competitive analysis]] of [[online algorithms]]. Given a set of items in a list where the cost of accessing an item is pr ...nit cost for exchanging any two adjacent items in the list. Performance of algorithms depend on the construction of request sequences by adversaries under variou ...

| title = Ultraconservative Online Algorithms for Multiclass Problems </ref> is a [[machine learning]] algorithm, an [[online algorithm]] for [[multiclass classification]] problems. It is designed to l ...

== Efficient algorithms == == Online algorithms == ...

...019}}{{Short description|Description of limiting behavior in probabilistic algorithms}} ...thm for verifying matrix multiplication. It runs faster than deterministic algorithms WHP. ...

...ccessible O'Rourke has made a pdf version of the book available online.{{r|online}} ...overing problems|coverings of polygons]], triangulations and triangulation algorithms, and higher-dimensional generalizations,{{r|edels}} including the result th ...

...] in 1987.<ref name=":22">{{cite arXiv |last1=Jiang |first1=Haotian |title=Online Geometric Discrepancy for Stochastic Arrivals with Applications to Envy Min ...rary.wiley.com/doi/abs/10.1002/rsa.3240010208 |journal=Random Structures & Algorithms |language=en |volume=1 |issue=2 |pages=215–220 |doi=10.1002/rsa.3240010208 ...

...in P. |last4=Ye |first4=Christopher |date=2024 |title=On the Complexity of Algorithms with Predictions for Dynamic Graph Problems |journal=Itcs '24 |pages=62:1–6 The '''online vector-matrix-vector problem''' (OuMv) is a variant of OMv where the algori ...

...r | first1 = Michael | last2 = Vassilvitskii | first2 = Sergei | chapter = Algorithms with Predictions | date = 31 December 2020 | pages = 646–662 | publisher = ...gular algorithms just the problem instance is inputted, learning augmented algorithms accept an extra parameter. ...

...rness]], and [[inapproximability]].{{r|appointed}} She holds the chair for Algorithms and Data Structures in the Computer Science Department at [[Heinrich Heine ...([[Dr. rer. nat.]]) in 2014 with the dissertation ''Coresets and streaming algorithms for the {{nowrap|<math>k</math>-means}} problem and related clustering obje ...

In the theory of [[online algorithm]]s and [[optimal stopping]], a '''prophet inequality''' is a boun ...E}[\max_i X_i]</math>.}} The prophet inequality states the existence of an online algorithm for this process whose expected value is at least half that of th ...

{{Short description|Class of greedy algorithms for multiway number partitioning}} ...such that the sums in the subsets are as nearly equal as possible. Greedy algorithms process the numbers sequentially, and insert the next number into a bin in ...

|title=cos 521: Advanced Algorithm Design Lecture 24: Online Algorithms Many [[online problem]]s have a sub-problem called the rent-or-buy problem. Given an expe ...

'''Harmonic bin-packing''' is a family of [[online algorithm]]s for [[bin packing]]. The input to such an algorithm is a list The harmonic bin-packing algorithms rely on partitioning the items into categories based on their sizes, follow ...

..., [[k-means clustering|k-means]] is a widely used heuristic but alternate algorithms have also been developed such as [[k-medoids]], [[CURE data clustering algo == Algorithms == ...

'''Best-fit''' is an [[online algorithm]] for [[bin packing]]. Its input is a list of items of different ...cking.pdf Worst-Case Performance Bounds for Simple One-Dimensional Packing Algorithms]. SICOMP, Volume 3, Issue 4. 1974.</ref> ...

'''Next-fit''' is an [[online algorithm]] for [[bin packing]]. Its input is a list of items of different ...rnal|last1=Johnson|first1=David S|date=1973|title=Near-optimal bin packing algorithms|url=https://dspace.mit.edu/bitstream/handle/1721.1/57819/17595570-MIT.pdf?s ...

{{confuse|online and offline}} ...ediction of prices in the financial international markets. Online learning algorithms may be prone to [[catastrophic interference]], a problem that can be addres ...

...more than two classes, some are by nature [[Binary classification|binary]] algorithms; these can, however, be turned into multinomial classifiers by a variety of ...g binary classifiers to solve multi-class classification problems. Several algorithms have been developed based on [[neural networks]], [[decision trees]], [[k-n ...

...s equivalent to the [[partition problem]]. However, there are optimization algorithms that can yield good results in practice. == Online minimization of the envy-difference == ...