Abstract: We study the complexity of equilibrium computation in discrete preference games.

Abstract: Machine learning algorithms are getting used increasingly in making decisions in domains with social consequences. This leads to a natural concern about the biases the algorithms might learn from possibly biased historical data.

Abstract: A complex number z is said to be algebraic, if there is a univariate f(x) with real coefficients such that f(z)=0. For instance i, the square root of -1, is algebraic with f(x) being x^2 + 1.

Abstract: Decision trees form a basic model of computation, with connections to many areas in complexity and approximation theory.

Abstract: We analyse the equilibrium behaviour of a large network of banks in presence of incomplete information, where inter-bank borrowing and lending is allowed, and banks suffer shocks to assets.