Search Results for author:
Found 10 papers, 0 papers with code
MAC Advice for Facility Location Mechanism Design
We study the $k$-facility location mechanism design problem, where the $n$ agents are strategic and might misreport their location.
Early Fusion of Features for Semantic Segmentation
The results demonstrate the effectiveness of our proposed model in achieving high segmentation accuracy, indicating its potential for various applications in image analysis.
Improving Length-Generalization in Transformers via Task Hinting
For sorting we show that it is possible to train models on data consisting of sequences having length at most $20$, and improve the test accuracy on sequences of length $100$ from less than 1% (for standard training) to more than 92% (via task hinting).
Spatiotemporal Filtering for Event-Based Action Recognition
In this work we introduce spatiotemporal filtering in the spike-event domain, as an alternative way of channeling spatiotemporal information through to a convolutional neural network.
Spatiotemporal Feature Learning for Event-Based Vision
Unlike conventional frame-based sensors, event-based visual sensors output information through spikes at a high temporal resolution.
Better Algorithms for Stochastic Bandits with Adversarial Corruptions
We study the stochastic multi-armed bandits problem in the presence of adversarial corruption.
Potential-Function Proofs for First-Order Methods
This note discusses proofs for convergence of first-order methods based on simple potential-function arguments.
Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration
We provide a novel instance-wise lower bound for the sample complexity of the problem, as well as a nontrivial sampling algorithm, matching the lower bound up to a factor of $\ln|\mathcal{F}|$.
Pure Exploration of Multi-armed Bandit Under Matroid Constraints
In a Best-Basis instance, we are given $n$ stochastic arms with unknown reward distributions, as well as a matroid $\mathcal{M}$ over the arms.
Differentially Private Combinatorial Optimization
Is it even possible to design good algorithms for this problem that preserve the privacy of the clients?
Data Structures and Algorithms Cryptography and Security Computer Science and Game Theory
