Browsing AI Memos (1959 - 2004) by Author "Jaakkola, Tommi"

Now showing items 1-4 of 4

    • Generalized Low-Rank Approximations 

      Srebro, Nathan; Jaakkola, Tommi (2003-01-15)
      We study the frequent problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving {\\em weighted} low rank approximation problems, which, unlike simple ...

    • Mean Field Theory for Sigmoid Belief Networks 

      Saul, Lawrence K.; Jaakkola, Tommi; Jordan, Michael I. (1996-08-01)
      We develop a mean field theory for sigmoid belief networks based on ideas from statistical mechanics. Our mean field theory provides a tractable approximation to the true probability distribution in these networks; it ...

    • On the Convergence of Stochastic Iterative Dynamic Programming Algorithms 

      Jaakkola, Tommi; Jordan, Michael I.; Singh, Satinder P. (1993-08-01)
      Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms, including the TD(lambda) algorithm of Sutton ...

    • Stable Mixing of Complete and Incomplete Information 

      Corduneanu, Adrian; Jaakkola, Tommi (2001-11-08)
      An increasing number of parameter estimation tasks involve the use of at least two information sources, one complete but limited, the other abundant but incomplete. Standard algorithms such as EM (or em) used in this context ...