# DEI on Wednesday

## Sparse Attention Mechanisms for Natural Language Processing

access_time April 22, 2020 at 01:30PM
place Videoconference
face André Martins

## Robust Revenue Maximization Under Minimal Statistical Information

We study the problem of multi-dimensional revenue maximization when selling $m$ items to a buyer that has additive valuations for them, drawn from a (possibly correlated) prior distribution. Unlike traditional Bayesian auction design, we assume that the seller has a very restricted knowledge of this prior: they only know the mean $\mu_j$ and an upper bound $\sigma_j$ on the standard deviation of each item's marginal distribution. Our goal is to design mechanisms that achieve good revenue against an ideal optimal auction that has full knowledge of the distribution in advance. We show that selling the items via separate price lotteries achieves an $O(\log r)$ approximation ratio where $r=\max_j(\sigma_j/\mu_j)$ is the maximum coefficient of variation across the items. If forced to restrict ourselves to deterministic mechanisms, this guarantee degrades to $O(r^2)$. Assuming independence of the item valuations, these ratios can be further improved by pricing the full bundle. We demonstrate the optimality of the above mechanisms by providing matching lower bounds. Our tight analysis for the deterministic case resolves an open gap from the work of Azar and Micali [ITCS'13]. As a by-product, we also show how one can directly use our upper bounds to improve and extend previous results related to the parametric auctions of Azar et al. [SODA'13]. This talk is based on joint work with Yiannis Giannakopoulos and Alexandros Tsigonias-Dimitriadis.

access_time April 01, 2020 at 01:00PM
place Videoconference
face Diogo Poças

## Designing for Emotional Meaning-Making with Data

From Fitbit to Apple Watch to sensors embedded in walls, furniture, and underwear, an amassing amount of biosensory data about people's bodies, behaviors, thoughts, and feelings presents sense-making challenges and opportunities. While prevalent approaches leverage data analysis to promote individual productivity and normative wellness, my design research contributes alternative design tactics for engaging biosensory data to more effectively support social, embodied, and emotional meaning-making. I will demonstrate this concept through two projects. The first, color-changing garment Ripple, explores how ambiguity can be a valuable design tactic for inviting open-ended social emotional reflection. I created ordinary-looking shirts with embedded biosensors and display elements, and studied how pairs of friends interpreted the display throughout their daily lives. My second project, the Heart Sounds Bench, explores life-affirmation as an alternative design frame for public sensing. I created a bench that amplifies the live unfiltered heart sounds of bench-sitters, and studied how pairs of strangers experienced listening to their heart sounds emanate into the environment. Through this, I envision critically reworking conceptions of sensing and data to support different ways of knowing.

access_time March 11, 2020 at 01:30PM
place Videoconference
face Noura Howell

## On the Evolution and Quality of Requirements: Industry’s Reality and Academia’s Efforts

Requirements models have been developed for the requirements engineers and stakeholders work, providing abstraction mechanisms to, for example, facilitate the communication among them by providing better structuring of requirements, thus helping with their analysis. Nevertheless, the extent to which requirements modelling languages are used and adequate for communication purposes has been somewhat limited. On one hand we firstly performed a study of the evolution of requirements practices in industry, particularly of software startups as they grow and introduce new products and services. These startups operate in a dynamic environment, with significant time and market pressure, and rarely have time for systematic requirements analysis. We describe the evolution of practice along some dimensions (e.g. requirements artefacts, product quality) that emerged as relevant to their requirements activities. We provide a theory that organises knowledge about evolving requirements practice in maturing startups, and provides practical insights for startups’ assessing their own evolution as they face challenges to their growth. On the other hand, from the academia’s perspective, we have studied several quality aspects, ranging from lack of abstraction mechanisms to address model’s complexity, to the impact of layout of models or the actual notation adopted. So, in this talk, I will discuss these issues based on the application of Grounded Theory (in the study of requirements and startups) and the results of experiments where metrics were collected to evaluate and discuss some quality aspects of requirements models, in particular requirements goal models (increasingly popular in the requirements community).

access_time March 04, 2020 at 01:30PM
place Alameda - Sala José Tribolet (0.19) - Pavilhão Informática II | TagusPark - Sala 2N1.5 (through videoconference)
face João Araújo