Online Learning of Non-stationary Sequences

We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them as simple Bayesian algorithms operating on models analogous to Hidden Markov Models (HMMs). We derive a new performance bound for such algorithms which is considerably simpler than existing bounds. The bound provides the basis for learning the rate at which the identity of the optimal expert switches over time. We find an analytic expression for the a priori resolution at which we need to learn the rate parameter. We extend our scalar switching-rate result to models of the switching-rate that are governed by a matrix of parameters, i.e. arbitrary homogeneous HMMs. We apply and examine our algorithm in the context of the problem of energy management in wireless networks. We analyze the new results in the framework of Information Theory.

Association Behavior of Biotinylated and Non-Biotinylated PolyEthylene Oxide-b-Poly(2-(Diethylamino)Ethyl Methacrylate)

Biotinylated and non-biotinylated copolymers of ethylene oxide (EO) and 2-(diethylamino)ethyl methacrylate (DEAEMA) were synthesized by the atom transfer radical polymerization technique (ATRP). The chemical compositions of the copolymers as determined by NMR are represented by PEO₁₁₃PDEAEMA₇₀ and biotin-PEO₁₀₄PDEAEMA₉₃ respectively. The aggregation behavior of these polymers in aqueous solutions at different pHs and ionic strengths was studied using a combination of potentiometric titration, dynamic light scattering (DLS), static light scattering (SLS), and transmission electron microscopy (TEM). Both PEO-b-PDEAEMA and biotin-PEO-b-PDEAEMA diblock copolymers form micelles at high pH with hydrodynamic radii (Rh) of about 19 and 23 nm, respectively. At low pH, the copolymers are dispersed as unimers in solution with Rh of about 6-7 nm. However, at a physiological salt concentration (cs) of about 0.16M NaCl and a pH of 7-8, the copolymers form large loosely packed Guassian chains, which were not present at the low cs of 0.001M NaCl. The critical micelle concentrations (CMC) and the cytotoxicity of the copolymers were investigated to determine a suitable polymer concentration range for future biological applications. Both PEO-b-PDEAEMA and biotin-PEO-b-PDEAEMA diblock copolymers possess identical CMC values of about 0.0023 mg/g, while the cytotoxicity test indicated that the copolymers are not toxic up to 0.05mg/g (> 83% cell survival at this concentration).