Speranza: Usable, privacy-friendly software signing
Software repositories, used for wide-scale open software distribu- tion, are a significant vector for security attacks. Software signing provides authenticity, mitigating many such attacks. Developer- managed signing keys ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)How Can Large Language Models Help Humans in Design And Manufacturing?
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Counterfactual Explanations and Predictive Models to Enhance Clinical Decision-Making in Schizophrenia using Digital Phenotyping
Clinical practice in psychiatry is burdened with the increased demand for healthcare services and the scarce resources available. New paradigms of health data powered with machine learning techniques could open the possibility ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Automated Exposure Notification for COVID-19
Private Automated Contact Tracing (PACT) was a collaborative team and effort formed during the beginning of the Coronavirus Disease 2019 (COVID-19) pandemic. PACT’s mission was to enhance contact tracing in pandemic response ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Neurosymbolic Programming for Science
Neurosymbolic Programming (NP) techniques have the potential to accelerate scientific discovery across fields. These models combine neural and symbolic components to learn complex patterns and representations from data, ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Universal Motion Generator: Trajectory Autocompletion by Motion Prompts
Foundation models, which are large neural networks trained on massive datasets, have shown impressive generalization in both the language and the vision domain. While fine-tuning foundation models for new tasks at test-time ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Active Loop Detection for Applications that Access Databases
We present Shear, a new system that observes and manipulates the interaction between an application and its surrounding environment to learn a model of the behavior of the application. Shear implements active loop detection ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Active Loop Detection for Applications that Access Databases
We present Shear, a new system that observes and manipulates the interaction between an application and its surrounding environment to learn a model of the behavior of the application. Shear implements active loop detection ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Bucket Elimination Algorithm for Dynamic Controllability Checking of Simple Temporal Networks with Uncertainty
Simple Temporal Networks with Uncertainty (STNU) can represent temporal problems where duration between events may be uncontrollable, e.g. when the event is caused by nature. An STNU is dynamically controllable (DC) if it ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Lower Bounds on the Column Sparsity of Compressed Sensing Matrices
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Precise and Comprehensive Provenance Tracking for Android Devices
Detailed information about the paths that data take through a system is invaluable for understanding sources and behaviors of complex exfiltration malware. We present a new system, ClearScope, that tracks, at the level of ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Comprehensive Java Metadata Tracking for Attack Detection and Repair
We present ClearTrack, a system that tracks 32 bits of metadata for each primitive value in Java programs to detect and nullify a range of vulnerabilities such as integer overflow and underflow vulnerabilities, SQL injection ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Generating Component-based Supervised Learning Programs From Crowdsourced Examples
We present CrowdLearn, a new system that processes an existing corpus of crowdsourced machine learning programs to learn how to generate effective pipelines for solving supervised machine learning problems. CrowdLearn uses ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)An Efficient Fill Estimation Algorithm for Sparse Matrices and Tensors in Blocked Formats
Tensors, linear-algebraic extensions of matrices in arbitrary dimensions, have numerous applications in computer science and computational science. Many tensors are sparse, containing more than 90% zero entries. Efficient ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Multi-Unit Auction Revenue with Possibilistic Beliefs
The revenue of traditional auction mechanisms is benchmarked solely against the players' own valuations, despite the fact that they may also have valuable beliefs about each other's valuations. Not much is known about ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Inference and Regeneration of Programs that Store and Retrieve Data
As modern computation platforms become increasingly complex, their programming interfaces are increasingly difficult to use. This complexity is especially inappropriate given the relatively simple core functionality that ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Guaranteeing Spoof-Resilient Multi-Robot Networks
Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)Does invariant recognition predict tuning of neurons in sensory cortex?
Tuning properties of simple cells in cortical V1 can be described in terms of a "universal shape" characterized by parameter values which hold across different species. This puzzling set of findings begs for a general ...
MIT Computer Science and Artificial Intelligence Lab (CSAIL)