The "nearest neighbor (NN) classifier" labels a new data instance by taking a majority vote over the k most similar instances seen in the past. With an appropriate setting of k, it is capable of modeling arbitrary decision rules.
Over the last three decades, the online bipartite matching (OBM) problem has emerged as a central problem in the area of Online Algorithms. Perhaps even more important is its role in the area of Matching-Based Market Design.
Partial function extension is a basic problem that underpins multiple research topics in optimization, including learning, property testing, and game theory.
Algebraic Complexity Theory is a field in which one studies complexity theoretic questions surrounding algebraic objects. In this talk we will be broadly discussing two such problems.
Many low- and middle-income countries face limited supply of vaccines. In such situations it is imperative to devise vaccination rollout strategies that maximize the cost-effectiveness of these limited vaccine stocks.
In a secure multi-party computation problem, players are required to compute a function of their private inputs without revealing any extra information about this input to other players.
You have n candidates to fill up n vacant positions in an office. The question is which candidate gets which position? To decide this, you ask non-candidates to vote. There are n!