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07/15/2023
Intuitive Access to Smartphone Settings Using Relevance Model Trained by Contrastive Learning
The more new features that are being added to smartphones, the harder it...
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07/12/2023
Mini-Batch Optimization of Contrastive Loss
Contrastive learning has gained significant attention as a method for se...
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07/07/2023
Teaching Arithmetic to Small Transformers
Large language models like GPT-4 exhibit emergent capabilities across ge...
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05/25/2023
Vector-Valued Variation Spaces and Width Bounds for DNNs: Insights on Weight Decay Regularization
Deep neural networks (DNNs) trained to minimize a loss term plus the sum...
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05/25/2023
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Learning from human feedback has been shown to improve text-to-image mod...
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05/08/2023
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation
In this paper, we propose MPC (Modular Prompted Chatbot), a new approach...
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02/05/2023
Improving Fair Training under Correlation Shifts
Model fairness is an essential element for Trustworthy AI. While many te...
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01/31/2023
Optimizing DDPM Sampling with Shortcut Fine-Tuning
In this study, we propose Shortcut Fine-tuning (SFT), a new approach for...
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01/30/2023
Looped Transformers as Programmable Computers
We present a framework for using transformer networks as universal compu...
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12/13/2022
Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance
Score-based generative models are shown to achieve remarkable empirical ...
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10/13/2022
Outlier-Robust Group Inference via Gradient Space Clustering
Traditional machine learning models focus on achieving good performance ...
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10/13/2022
Equal Improvability: A New Fairness Notion Considering the Long-term Impact
Devising a fair classifier that does not discriminate against different ...
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10/06/2022
A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets
Weight decay is one of the most widely used forms of regularization in d...
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06/14/2022
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks
Fine-tuning pretrained language models (LMs) without making any architec...
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05/23/2022
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
Word translation without parallel corpora has become feasible, rivaling ...
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04/12/2022
Breaking Fair Binary Classification with Optimal Flipping Attacks
Minimizing risk with fairness constraints is one of the popular approach...
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02/24/2022
Rare Gems: Finding Lottery Tickets at Initialization
It has been widely observed that large neural networks can be pruned to ...
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01/07/2022
Improved Input Reprogramming for GAN Conditioning
We study the GAN conditioning problem, whose goal is to convert a pretra...
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01/07/2022
GenLabel: Mixup Relabeling using Generative Models
Mixup is a data augmentation method that generates new data points by mi...
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12/07/2021
Augment Valuate : A Data Enhancement Pipeline for Data-Centric AI
Data scarcity and noise are important issues in industrial applications ...
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10/29/2021
Improving Fairness via Federated Learning
Recently, lots of algorithms have been proposed for learning a fair clas...
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10/28/2021
Gradient Inversion with Generative Image Prior
Federated Learning (FL) is a distributed learning framework, in which th...
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10/27/2021
Sample Selection for Fair and Robust Training
Fairness and robustness are critical elements of Trustworthy AI that nee...
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06/11/2021
Coded-InvNet for Resilient Prediction Serving Systems
Inspired by a new coded computation algorithm for invertible functions, ...
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02/19/2021
Permutation-Based SGD: Is Random Optimal?
A recent line of ground-breaking results for permutation-based SGD has c...
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12/03/2020
FairBatch: Batch Selection for Model Fairness
Training a fair machine learning model is essential to prevent demograph...
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10/30/2020
SLM: Learning a Discourse Language Representation with Sentence Unshuffling
We introduce Sentence-level Language Modeling, a new pre-training object...
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10/29/2020
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification
Distributed model training suffers from communication bottlenecks due to...
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07/09/2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Due to its decentralized nature, Federated Learning (FL) lends itself to...
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03/16/2020
Discrete-valued Preference Estimation with Graph Side Information
Incorporating graph side information into recommender systems has been w...
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02/24/2020
FR-Train: A mutual information-based approach to fair and robust training
Trustworthy AI is a critical issue in machine learning where, in additio...
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05/23/2018
Hypergraph Spectral Clustering in the Weighted Stochastic Block Model
Spectral clustering is a celebrated algorithm that partitions objects ba...
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01/15/2018
Hierarchical Coding for Distributed Computing
Coding for distributed computing supports low-latency computation by rel...
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11/26/2017
Simulating outcomes of interventions using a multipurpose simulation program based on the Evolutionary Causal Matrices and Markov Chain
Predicting long-term outcomes of interventions is necessary for educatio...
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09/12/2017
