7 accepted papers
A seminal work by Moulin (1980) shows that the median voting scheme fully characterizes (deterministic) strategy-proof facility location mechanism for single-peaked preferences. In this simple setting, median also achieves the optimal social cost. In $d$ dimensions, strategy-proof mechanism is chara…
Truncated linear regression is a classical challenge in Statistics, wherein a label, $y = w^T x + \varepsilon$, and its corresponding feature vector, $x \in \mathbb{R}^k$, are only observed if the label falls in some subset $S \subseteq \mathbb{R}$; otherwise the existence of the pair $(x, y)$ is hi…
We study the problem of learning revenue-optimal multi-bidder auctions from samples when the samples of bidders' valuations can be adversarially corrupted or drawn from distributions that are adversarially perturbed. First, we prove tight upper bounds on the revenue we can obtain with a corrupted di…
Machine learning and statistics are invaluable for extracting insights from data. A key assumption of most methods, however, is that they have access to independent samples from the distribution of relevant data. As such, these methods often perform poorly in the face of {\em biased data} which brea…
Generative neural networks have been empirically found very promising in providing effective structural priors for compressed sensing, since they can be trained to span low-dimensional data manifolds in high-dimensional signal spaces. Despite the non-convexity of the resulting optimization problem,…
respect to the Renyi Divergence, which provides improved theoretical and practical results in differentially private submodular optimization.
As in standard linear regression, in truncated linear regression, we are given access to observations (A