computer science

Nicolò Cesa-Bianchi

Nicolò Cesa-Bianchi is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Nicolò Cesa-Bianchi rather than just read about it. In short: Nicolò Cesa-Bianchi (Italian pronunciation: [nikoˈlɔ tˈtʃɛːza ˈbjaŋki]) is an Italian computer scientist and Professor of Computer Science at the Department of Computer Science of the University of Milan. He is a researcher in the field of machine learning, and co-author of the books "Prediction, Learning, and Games" with Gabor Lugosi and "Regret analysis of stochastic and nonstochastic multi-armed bandit problems"…

Key takeaways

Nicolò Cesa-Bianchi belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Nicolò Cesa-Bianchi to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Nicolò Cesa-Bianchi from memory before moving on to harder problems.

Reference excerpt

Nicolò Cesa-Bianchi (Italian pronunciation: [nikoˈlɔ tˈtʃɛːza ˈbjaŋki]) is an Italian computer scientist and Professor of Computer Science at the Department of Computer Science of the University of Milan. He is a researcher in the field of machine learning, and co-author of the books "Prediction, Learning, and Games" with Gabor Lugosi and "Regret analysis of stochastic and nonstochastic multi-armed bandit problems" with Sébastien Bubeck

Education and career Cesa-Bianchi graduated in Computer Science from the University of Milan in 1988 where he received a PhD in Computer Science in 1993 supervised by Alberto Bertoni. During his PhD, he visited UC Santa Cruz where he worked with Manfred Warmuth and David Haussler. He did his postdoctoral studies at Graz University of Technology under the supervision of Wolfgang Maass.

Research His research contributions focus on the following areas:

design and analysis of machine learning algorithms, especially in online machine learning algorithms for multi-armed bandit problems, with applications to recommender systems and online auctions graph analytics, with applications to social networks and bioinformatics

Awards and honors Cesa-Bianchi received a Google Research Award in 2010, a Xerox University Affairs Committee Award in 2011, a Criteo Faculty Award in 2017, a Google Faculty Award in 2018, and a IBM Academic Award in 2021. Since 2023 he is corresponding member of the Accademia dei Lincei.

References

Illustrations

Worked examples

Example 1 — a first encounter with Nicolò Cesa-Bianchi

Start with the simplest possible case. Write down what Nicolò Cesa-Bianchi claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Nicolò Cesa-Bianchi before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Nicolò Cesa-Bianchi ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Nicolò Cesa-Bianchi

In research: Nicolò Cesa-Bianchi appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Nicolò Cesa-Bianchi in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Nicolò Cesa-Bianchi is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1963 births, Academic staff of the University of Milan, Computer scientist stubs, so understanding it makes those chapters shorter.
In everyday life: Look for Nicolò Cesa-Bianchi outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Nicolò Cesa-Bianchi in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Nicolò Cesa-Bianchi means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Nicolò Cesa-Bianchi out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nicolò Cesa-Bianchi in simple terms?

Why does Nicolò Cesa-Bianchi matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Nicolò Cesa-Bianchi?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Nicolò Cesa-Bianchi.