Italy

IMPROVE is a comprehensive conference of academic and technical nature, focused on image processing and computer vision practical applications. It brings together researchers, engineers and practitioners working either in fundamental areas of image processing, developing new methods and techniques, including innovative machine learning approaches, as well as multimedia communications technology and applications of image processing and artificial vision in diverse areas.

IMPROVE 2022

EMNLP 2021 is planned to be a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation possible. The experience for on-site participants would closely approximate a normal pre-COVID *ACL conference, with 5-6 thematically organized parallel sessions and live Q/A and interactive discussion immediately after the talks. Presentations by virtual participants will be equitably interleaved with those of on-site participants, projected on the auditorium screens as if on-site, and also followed immediately by live Q/A and interactive discussion at a time during reasonable waking hours for the virtual presenter. For all participants, on-site and virtual, who are unable to attend a session due to either time-zone issues or because they are participating in another session live, talk recordings and slides will be available online at a minimum after the live presentation (and in many cases before as well), and questions may be submitted in advance on session-specific discussion boards and answered live in session with the usual visual aids if desired.

<iframe style="width:700px;height:400px" src="https://online.fliphtml5.com/ebtyf/ceby/"  seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe>

Please Note: The EMNLP registration system is not currently connected to the underline site as we are still in the process of building out EMNLP 2021. You will receive access instructions from underline the week of November 1st. 

Access is given only to EMNLP upon registration, if you have not registered please do so [here](https://2021.emnlp.org/registration).

EMNLP 2021

EMNLP 2021 is planned to be a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation possible.

In 1948, Shannon published a famous paper, which laid the foundations of information theory and led to a revolution in communication technologies. Critical to Shannon’s ideas was the notion that a signal can be represented in terms of “bits,” and that the information content of the signal can be measured by the minimum expected number of bits. However, while such a notion of information is well suited for tasks such as signal compression and reconstruction, it is not directly applicable to audio-visual scene interpretation tasks, because bits do not depend on the “semantic content” of the signal, such as words in a document, or objects in an image. In this talk, I will present a new measure of semantic information content called “semantic entropy”, which is defined as the minimum expected number of semantic queries about the data whose answers are sufficient for solving a given task (e.g., classification). I will also present an information-theoretic framework called ``information pursuit'' for deciding which queries to ask and in which order, which requires a probabilistic generative model relating data and questions to the task. Experiments on handwritten digit classification show, for example, that the translated MNIST dataset is harder to classify than the MNIST dataset. Joint work with Aditya Chattopadhyay, Benjamin Haeffele and Donald Geman.

Premium content

Semantic Information Pursuit

Next from IMPROVE 2022

Robust Fitting in Computer Vision

Similar lectures

Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP