Optimal change-point estimation from indirect observations

We study nonparametric change-point estimation from indirect noisy observations. Focusing on the white noise convolution model, we consider two classes of functions that are smooth apart from the change-point. We establish lower bounds on the minimax risk in estimating the change-point and develop rate optimal estimation procedures. The results demonstrate that the best achievable rates of convergence are determined both by smoothness of the function away from the change-point and by the degree of ill-posedness of the convolution operator. Optimality is obtained by introducing a new technique that involves, as a key element, detection of zero crossings of an estimate of the properly smoothed second derivative of the underlying function.Comment: Published at http://dx.doi.org/10.1214/009053605000000750 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Non-stationary Stochastic Optimization

We consider a non-stationary variant of a sequential stochastic optimization problem, in which the underlying cost functions may change along the horizon. We propose a measure, termed variation budget, that controls the extent of said change, and study how restrictions on this budget impact achievable performance. We identify sharp conditions under which it is possible to achieve long-run-average optimality and more refined performance measures such as rate optimality that fully characterize the complexity of such problems. In doing so, we also establish a strong connection between two rather disparate strands of literature: adversarial online convex optimization; and the more traditional stochastic approximation paradigm (couched in a non-stationary setting). This connection is the key to deriving well performing policies in the latter, by leveraging structure of optimal policies in the former. Finally, tight bounds on the minimax regret allow us to quantify the "price of non-stationarity," which mathematically captures the added complexity embedded in a temporally changing environment versus a stationary one

In vitro immunosuppressive effects of FR 900506 on human T lymphocyte alloactivation

FR 900506 (FR) is a new immunosuppressive drug which prolongs allograft survival. Our studies have compared the in vitro inhibitory effects of FR and cyclosporine (CsA) on human lymphocyte proliferation. Considerably lower doses of FR were required to induce inhibition of lymphocyte proliferation induced by concanavalin A (Con A) stimulation or in primary mixed lymphocyte reactions (MLR). Similar differences between FR and CsA were observed with the secondary stimulation of alloactivated T cells generated in MLR or propagated from liver transplant biopsies. These observations provide further evidence that FR is about 500 fold more potent than CsA and may be a useful immunosuppressive agent in organ transplantation