1 code implementation • ECCV 2018 • Sujoy Paul, Sourya Roy, Amit K. Roy-Chowdhury
Most activity localization methods in the literature suffer from the burden of frame-wise annotation requirement.
Ranked #1 on Action Classification on ActivityNet-1.2
1 code implementation • 6 Mar 2019 • Jawadul H. Bappy, Cody Simons, Lakshmanan Nataraj, B. S. Manjunath, Amit K. Roy-Chowdhury
This paper proposes a high-confidence manipulation localization architecture which utilizes resampling features, Long-Short Term Memory (LSTM) cells, and encoder-decoder network to segment out manipulated regions from non-manipulated ones.
1 code implementation • ICMR 2018 • Niluthpol Chowdhury Mithun, Juncheng Li, Florian Metze, Amit K. Roy-Chowdhury
Constructing a joint representation invariant across different modalities (e. g., video, language) is of significant importance in many multimedia applications.
Ranked #37 on Video Retrieval on MSR-VTT
2 code implementations • CVPR 2016 • Mahmudul Hasan, Jonghyun Choi, Jan Neumann, Amit K. Roy-Chowdhury, Larry S. Davis
Perceiving meaningful activities in a long video sequence is a challenging problem due to ambiguous definition of 'meaningfulness' as well as clutters in the scene.
Ranked #2 on Traffic Accident Detection on A3D
1 code implementation • CVPR 2021 • Sk Miraj Ahmed, Dripta S. Raychaudhuri, Sujoy Paul, Samet Oymak, Amit K. Roy-Chowdhury
A recent line of work addressed this problem and proposed an algorithm that transfers knowledge to the unlabeled target domain from a single source model without requiring access to the source data.
1 code implementation • CVPR 2019 • Niluthpol Chowdhury Mithun, Sujoy Paul, Amit K. Roy-Chowdhury
The weak nature of the supervision is because, during training, we only have access to the video-text pairs rather than the temporal extent of the video to which different text descriptions relate.
1 code implementation • 4 Oct 2022 • Hanzhe Teng, Dimitrios Chatziparaschis, Xinyue Kan, Amit K. Roy-Chowdhury, Konstantinos Karydis
Results demonstrate that our proposed CED keypoint detector requires minimal computational time while attaining high repeatability.
1 code implementation • CVPR 2018 • Shuyue Lan, Rameswar Panda, Qi Zhu, Amit K. Roy-Chowdhury
The first group is supported by video summarization techniques, which require processing of the entire video to select an important subset for showing to users.
1 code implementation • 3 Jul 2017 • Jason Bunk, Jawadul H. Bappy, Tajuddin Manhar Mohammed, Lakshmanan Nataraj, Arjuna Flenner, B. S. Manjunath, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, Lawrence Peterson
In this paper, we propose two methods to detect and localize image manipulations based on a combination of resampling features and deep learning.
1 code implementation • 4 Jun 2022 • Calvin-Khang Ta, Abhishek Aich, Akash Gupta, Amit K. Roy-Chowdhury
In this work, we explore a sparsity and dictionary learning-based approach and present a novel self-supervised learning method for single-image denoising where the noise is approximated as a Poisson process, requiring no clean ground-truth data.
1 code implementation • NeurIPS 2019 • Sujoy Paul, Jeroen van Baar, Amit K. Roy-Chowdhury
Learning to solve complex goal-oriented tasks with sparse terminal-only rewards often requires an enormous number of samples.
1 code implementation • NeurIPS 2021 • Shasha Li, Abhishek Aich, Shitong Zhu, M. Salman Asif, Chengyu Song, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
When compared to the image classification models, black-box adversarial attacks against video classification models have been largely understudied.
1 code implementation • ICCV 2023 • Cody Simons, Dripta S. Raychaudhuri, Sk Miraj Ahmed, Suya You, Konstantinos Karydis, Amit K. Roy-Chowdhury
In this work, we relax both of these assumptions by addressing the problem of adapting a set of models trained independently on uni-modal data to a target domain consisting of unlabeled multi-modal data, without having access to the original source dataset.
1 code implementation • 13 Aug 2020 • Akash Gupta, Rameswar Panda, Sujoy Paul, Jianming Zhang, Amit K. Roy-Chowdhury
While machine learning approaches to visual recognition offer great promise, most of the existing methods rely heavily on the availability of large quantities of labeled training data.
1 code implementation • CVPR 2020 • Abhishek Aich, Akash Gupta, Rameswar Panda, Rakib Hyder, M. Salman Asif, Amit K. Roy-Chowdhury
Different from these methods, we focus on the problem of generating videos from latent noise vectors, without any reference input frames.
1 code implementation • 29 Jul 2021 • Akash Gupta, Abhishek Aich, Kevin Rodriguez, G. Venugopala Reddy, Amit K. Roy-Chowdhury
In this paper, we propose a data-driven Deep Quantized Latent Representation (DQLR) methodology for high-quality image reconstruction in the Shoot Apical Meristem (SAM) of Arabidopsis thaliana.
1 code implementation • 10 Aug 2020 • Shuyue Lan, Zhilu Wang, Amit K. Roy-Chowdhury, Ermin Wei, Qi Zhu
In many intelligent systems, a network of agents collaboratively perceives the environment for better and more efficient situation awareness.
1 code implementation • 9 Nov 2023 • Arindam Dutta, Rohit Lal, Dripta S. Raychaudhuri, Calvin Khang Ta, Amit K. Roy-Chowdhury
Human silhouette extraction is a fundamental task in computer vision with applications in various downstream tasks.
no code implementations • 9 Feb 2018 • Tajuddin Manhar Mohammed, Jason Bunk, Lakshmanan Nataraj, Jawadul H. Bappy, Arjuna Flenner, B. S. Manjunath, Shivkumar Chandrasekaran, Amit K. Roy-Chowdhury, Lawrence Peterson
Realistic image forgeries involve a combination of splicing, resampling, cloning, region removal and other methods.
no code implementations • 9 Jun 2017 • Rameswar Panda, Niluthpol Chowdhury Mithun, Amit K. Roy-Chowdhury
Most video summarization approaches have focused on extracting a summary from a single video; we propose an unsupervised framework for summarizing a collection of videos.
no code implementations • 9 Jun 2017 • Rameswar Panda, Amit K. Roy-Chowdhury
In this paper, with the aim of summarizing multi-view videos, we introduce a novel unsupervised framework via joint embedding and sparse representative selection.
no code implementations • CVPR 2017 • Rameswar Panda, Amit K. Roy-Chowdhury
Large collections of videos are grouped into clusters by a topic keyword, such as Eiffel Tower or Surfing, with many important visual concepts repeating across them.
no code implementations • CVPR 2017 • Rameswar Panda, Amran Bhuiyan, Vittorio Murino, Amit K. Roy-Chowdhury
Most approaches have neglected the dynamic and open world nature of the re-identification problem, where a new camera may be temporarily inserted into an existing system to get additional information.
no code implementations • 1 Aug 2016 • Rameswar Panda, Abir Das, Amit K. Roy-Chowdhury
While most existing video summarization approaches aim to extract an informative summary of a single video, we propose a novel framework for summarizing multi-view videos by exploiting both intra- and inter-view content correlations in a joint embedding space.
no code implementations • 25 Jul 2016 • Niki Martinel, Abir Das, Christian Micheloni, Amit K. Roy-Chowdhury
Person re-identification is an open and challenging problem in computer vision.
no code implementations • 1 Jul 2016 • Abir Das, Rameswar Panda, Amit K. Roy-Chowdhury
We demonstrate the effectiveness of our approach on multi-camera person re-identification datasets, to demonstrate the feasibility of learning online classification models in multi-camera big data applications.
no code implementations • 6 Aug 2018 • Sujoy Paul, Sourya Roy, Amit K. Roy-Chowdhury
This necessitates learning of visual features from videos in an unsupervised setting.
no code implementations • ECCV 2018 • Rameswar Panda, Jianming Zhang, Haoxiang Li, Joon-Young Lee, Xin Lu, Amit K. Roy-Chowdhury
While machine learning approaches to visual emotion recognition offer great promise, current methods consider training and testing models on small scale datasets covering limited visual emotion concepts.
no code implementations • 23 Aug 2018 • Niluthpol Chowdhury Mithun, Rameswar Panda, Evangelos E. Papalexakis, Amit K. Roy-Chowdhury
Inspired by the recent success of webly supervised learning in deep neural networks, we capitalize on readily-available web images with noisy annotations to learn robust image-text joint representation.
no code implementations • 27 Sep 2018 • Tahmida Mahmud, Mohammad Billah, Amit K. Roy-Chowdhury
Multi-view frame reconstruction is an important problem particularly when multiple frames are missing and past and future frames within the camera are far apart from the missing ones.
no code implementations • CVPR 2018 • Sourya Roy, Sujoy Paul, Neal E. Young, Amit K. Roy-Chowdhury
Minimization of labeling effort for person re-identification in camera networks is an important problem as most of the existing popular methods are supervised and they require large amount of manual annotations, acquiring which is a tedious job.
no code implementations • CVPR 2013 • Yingying Zhu, Nandita M. Nayak, Amit K. Roy-Chowdhury
This is motivated from the observations that the activities related in space and time rarely occur independently and can serve as the context for each other.
no code implementations • CVPR 2013 • Ahmed T. Kamal, Jay A. Farrell, Amit K. Roy-Chowdhury
The estimation errors in tracking and data association, as well as the effect of naivety, are jointly addressed leading to the development of an informationweighted consensus algorithm, which we term as the Multitarget Information Consensus (MTIC) algorithm.
no code implementations • CVPR 2014 • Mahmudul Hasan, Amit K. Roy-Chowdhury
Most of the state-of-the-art approaches to human activity recognition in video need an intensive training stage and assume that all of the training examples are labeled and available beforehand.
no code implementations • CVPR 2017 • Jawadul H. Bappy, Sujoy Paul, Ertem Tuncel, Amit K. Roy-Chowdhury
In computer vision, selection of the most informative samples from a huge pool of training data in order to learn a good recognition model is an active research problem.
no code implementations • ICCV 2015 • Mahmudul Hasan, Amit K. Roy-Chowdhury
We formulate a conditional random field (CRF) model that encodes the context and devise an information theoretic approach that utilizes entropy and mutual information of the nodes to compute the set of most informative query instances, which need to be labeled by a human.
no code implementations • ICCV 2017 • Rameswar Panda, Abir Das, Ziyan Wu, Jan Ernst, Amit K. Roy-Chowdhury
Casting the problem as a weakly supervised learning problem, we propose a flexible deep 3D CNN architecture to learn the notion of importance using only video-level annotation, and without any human-crafted training data.
no code implementations • ICCV 2017 • Jawadul H. Bappy, Amit K. Roy-Chowdhury, Jason Bunk, Lakshmanan Nataraj, B. S. Manjunath
In order to formulate the framework, we employ a hybrid CNN-LSTM model to capture discriminative features between manipulated and non-manipulated regions.
no code implementations • ICCV 2017 • Tahmida Mahmud, Mahmudul Hasan, Amit K. Roy-Chowdhury
We propose a network similar to a hybrid Siamese network with three branches to jointly learn both the future label and the starting time.
no code implementations • 15 Mar 2019 • Lakshmanan Nataraj, Tajuddin Manhar Mohammed, Shivkumar Chandrasekaran, Arjuna Flenner, Jawadul H. Bappy, Amit K. Roy-Chowdhury, B. S. Manjunath
The advent of Generative Adversarial Networks (GANs) has brought about completely novel ways of transforming and manipulating pixels in digital images.
no code implementations • 9 Apr 2019 • Mahmudul Hasan, Sujoy Paul, Anastasios I. Mourikis, Amit K. Roy-Chowdhury
We formulate a conditional random field model that encodes the context and devise an information-theoretic approach that utilizes entropy and mutual information of the nodes to compute the set of most informative queries, which are labeled by a human.
no code implementations • IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019 • Ghazal Mazaheri, Niluthpol Chowdhury Mithun, Jawadul H. Bappy, Amit K. Roy-Chowdhury
In order to exploit these traces in localizing the tampered regions, we propose an encoder-decoder based network where we fuse representations from early layers in the encoder (which are richer in low-level spatial cues, like edges) by skip pooling with representations of the last layer of the decoder and use for manipulation detection.
no code implementations • 2 Aug 2019 • Tahmida Mahmud, Mohammad Billah, Mahmudul Hasan, Amit K. Roy-Chowdhury
Most of the existing works on human activity analysis focus on recognition or early recognition of the activity labels from complete or partial observations.
no code implementations • 27 Aug 2019 • Xueping Wang, Rameswar Panda, Min Liu, Yaonan Wang, Amit K. Roy-Chowdhury
Additionally, a cross-view matching strategy followed by global camera network constraints is proposed to explore the matching relationships across the entire camera network.
no code implementations • Proceedings of the 26th ACM international conference on Multimedia·October 2018 2018 • Niluthpol Chowdhury Mithun, Rameswar Panda, Vagelis Papalexakis, Amit K. Roy-Chowdhury
Inspired by the recent success of web-supervised learning in deep neural networks, we capitalize on readily-available web images with noisy annotations to learn robust image-text joint representation.
no code implementations • 21 Jul 2020 • Xueping Wang, Sujoy Paul, Dripta S. Raychaudhuri, Min Liu, Yaonan Wang, Amit K. Roy-Chowdhury, Fellow, IEEE
In order to cope with this issue, we introduce the problem of learning person re-identification models from videos with weak supervision.
Multiple Instance Learning Video-Based Person Re-Identification
no code implementations • CVPR 2020 • Sk. Miraj Ahmed, Aske R Lejbølle, Rameswar Panda, Amit K. Roy-Chowdhury
Most of the existing approaches for person re-identification consider a static setting where the number of cameras in the network is fixed.
no code implementations • ECCV 2020 • Dripta S. Raychaudhuri, Amit K. Roy-Chowdhury
While supervised techniques in re-identification are extremely effective, the need for large amounts of annotations makes them impractical for large camera networks.
no code implementations • ECCV 2020 • Sujoy Paul, Yi-Hsuan Tsai, Samuel Schulter, Amit K. Roy-Chowdhury, Manmohan Chandraker
In this work, we propose a novel framework for domain adaptation in semantic segmentation with image-level weak labels in the target domain.
no code implementations • 20 Aug 2020 • Sudipta Paul, Niluthpol Chowdhury Mithun, Amit K. Roy-Chowdhury
This task poses a unique challenge as the system is required to perform: (i) retrieval of the relevant video where only a segment of the video corresponds with the queried sentence, and (ii) temporal localization of moment in the relevant video based on sentence query.
no code implementations • 26 Aug 2020 • Shasha Li, Karim Khalil, Rameswar Panda, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, Ananthram Swami
The emergence of Internet of Things (IoT) brings about new security challenges at the intersection of cyber and physical spaces.
no code implementations • 31 Aug 2020 • Akash Gupta, Abhishek Aich, Amit K. Roy-Chowdhury
Different from these works, we address a more realistic problem of high frame-rate sharp video synthesis with no prior assumption that input is always blurry.
no code implementations • 18 Oct 2020 • Sudipta Paul, Shivkumar Chandrasekaran, B. S. Manjunath, Amit K. Roy-Chowdhury
Several works in computer vision have demonstrated the effectiveness of active learning for adapting the recognition model when new unlabeled data becomes available.
no code implementations • 3 Feb 2021 • Ghazal Mazaheri, Kevin Urrutia Avila, Amit K. Roy-Chowdhury
We show that our method leads to a 90% accuracy rate of detecting duplicated images, a ~ 13% improvement in detection accuracy in comparison to other manipulation detection methods.
no code implementations • 15 Mar 2021 • Ghazal Mazaheri, Amit K. Roy-Chowdhury
Thus, it is important to develop methods that can detect manipulations in facial expressions, and localize the manipulated regions.
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • 20 May 2021 • Dripta S. Raychaudhuri, Sujoy Paul, Jeroen van Baar, Amit K. Roy-Chowdhury
Once this correspondence is found, we can directly transfer the demonstrations on one domain to the other and use it for imitation.
no code implementations • ICCV 2021 • Abhishek Aich, Meng Zheng, Srikrishna Karanam, Terrence Chen, Amit K. Roy-Chowdhury, Ziyan Wu
To alleviate these problems, we propose Spatio-Temporal Representation Factorization (STRF), a flexible new computational unit that can be used in conjunction with most existing 3D convolutional neural network architectures for re-ID.
Ranked #2 on Person Re-Identification on DukeMTMC-VideoReID
no code implementations • 31 Jul 2021 • Sayak Nag, Dripta S. Raychaudhuri, Sujoy Paul, Amit K. Roy-Chowdhury
However, it is a critical task in many applications like environmental monitoring, where the number of labeled examples for each class is limited.
no code implementations • 5 Aug 2021 • Akash Gupta, Padmaja Jonnalagedda, Bir Bhanu, Amit K. Roy-Chowdhury
Specifically, meta-learning is employed to obtain adaptive parameters, using a large-scale external dataset, that can adapt quickly to the novel condition (degradation model) of the given test video during the internal learning task, thereby exploiting external and internal information of a video for super-resolution.
no code implementations • ICCV 2021 • Mingjun Yin, Shasha Li, Zikui Cai, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
Vision systems that deploy Deep Neural Networks (DNNs) are known to be vulnerable to adversarial examples.
no code implementations • ICCV 2021 • Xueping Wang, Shasha Li, Min Liu, Yaonan Wang, Amit K. Roy-Chowdhury
The success of deep neural networks (DNNs) has promoted the widespread applications of person re-identification (ReID).
no code implementations • 24 Oct 2021 • Mingjun Yin, Shasha Li, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy
A very recent defense strategy for detecting adversarial examples, that has been shown to be robust to current attacks, is to check for intrinsic context consistencies in the input data, where context refers to various relationships (e. g., object-to-object co-occurrence relationships) in images.
no code implementations • 6 Dec 2021 • Zikui Cai, Xinxin Xie, Shasha Li, Mingjun Yin, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, M. Salman Asif
In this paper, we present a new approach to generate context-aware attacks for object detectors.
no code implementations • CVPR 2022 • Dripta S. Raychaudhuri, Yumin Suh, Samuel Schulter, Xiang Yu, Masoud Faraki, Amit K. Roy-Chowdhury, Manmohan Chandraker
In contrast to the existing dynamic multi-task approaches that adjust only the weights within a fixed architecture, our approach affords the flexibility to dynamically control the total computational cost and match the user-preferred task importance better.
no code implementations • CVPR 2022 • Zikui Cai, Shantanu Rane, Alejandro E. Brito, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, M. Salman Asif
We compare our zero-query attack against a few-query scheme that repeatedly checks if the victim system is fooled.
no code implementations • 2 Apr 2022 • Akash Gupta, Jingen Liu, Liefeng Bo, Amit K. Roy-Chowdhury, Tao Mei
To incorporate this ability in intelligent systems a question worth pondering upon is how exactly do we anticipate?
no code implementations • 8 Sep 2022 • Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Amit K. Roy-Chowdhury
In such cases, transferring knowledge from a neural network trained on a well-labeled large dataset in the source modality (RGB) to a neural network that works on a target modality (depth, infrared, etc.)
no code implementations • 20 Sep 2022 • Abhishek Aich, Shasha Li, Chengyu Song, M. Salman Asif, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury
Our goal is to design an attack strategy that can learn from such natural scenes by leveraging the local patch differences that occur inherently in such images (e. g. difference between the local patch on the object `person' and the object `bike' in a traffic scene).
no code implementations • 20 Sep 2022 • Abhishek Aich, Calvin-Khang Ta, Akash Gupta, Chengyu Song, Srikanth V. Krishnamurthy, M. Salman Asif, Amit K. Roy-Chowdhury
Using the joint image-text features to train the generator, we show that GAMA can craft potent transferable perturbations in order to fool victim classifiers in various attack settings.
no code implementations • 14 Oct 2022 • Sudipta Paul, Amit K. Roy-Chowdhury, Anoop Cherian
Similar to audio-visual navigation tasks, the goal of our embodied agent is to localize an audio event via navigating the 3D visual world; however, the agent may also seek help from a human (oracle), where the assistance is provided in free-form natural language.
no code implementations • 14 Dec 2022 • Abhishek Aich, Kuan-Chuan Peng, Amit K. Roy-Chowdhury
Most cross-domain unsupervised Video Anomaly Detection (VAD) works assume that at least few task-relevant target domain training data are available for adaptation from the source to the target domain.
no code implementations • 27 May 2023 • Shuyue Lan, Zhilu Wang, Ermin Wei, Amit K. Roy-Chowdhury, Qi Zhu
We show that compared with other approaches in the literature, our frameworks achieve better coverage of important frames, while significantly reducing the number of frames processed at each agent.
no code implementations • 10 Jul 2023 • Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen, Amit K. Roy-Chowdhury, Ananda Theertha Suresh, Samet Oymak
These insights on scale and modularity motivate a new federated learning approach we call "You Only Load Once" (FedYolo): The clients load a full PTF model once and all future updates are accomplished through communication-efficient modules with limited catastrophic-forgetting, where each task is assigned to its own module.
no code implementations • ICCV 2023 • Abhishek Aich, Samuel Schulter, Amit K. Roy-Chowdhury, Manmohan Chandraker, Yumin Suh
Further, we present a simple but effective search algorithm that translates user constraints to runtime width configurations of both the shared encoder and task decoders, for sampling the sub-architectures.
no code implementations • ICCV 2023 • Dripta S. Raychaudhuri, Calvin-Khang Ta, Arindam Dutta, Rohit Lal, Amit K. Roy-Chowdhury
To address this limitation, we focus on the task of source-free domain adaptation for pose estimation, where a source model must adapt to a new target domain using only unlabeled target data.
no code implementations • 20 Sep 2023 • Md Shazid Islam, Arindam Dutta, Calvin-Khang Ta, Kevin Rodriguez, Christian Michael, Mark Alber, G. Venugopala Reddy, Amit K. Roy-Chowdhury
Tracking of plant cells in images obtained by microscope is a challenging problem due to biological phenomena such as large number of cells, non-uniform growth of different layers of the tightly packed plant cells and cell division.
no code implementations • 8 Nov 2023 • Fahim Faisal Niloy, Sk Miraj Ahmed, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury
By restoring the knowledge from the source, it effectively corrects the negative consequences arising from the gradual deterioration of model parameters caused by ongoing shifts in the domain.
no code implementations • 5 Dec 2023 • Rohit Kundu, Sudipta Paul, Rohit Lal, Amit K. Roy-Chowdhury
Specifically, we propose an approach to enable the Segment Anything Model (SAM) with semantic recognition capability to generate pixel-level annotations for images without any manual supervision.
no code implementations • 8 Dec 2023 • Md Shazid Islam, Sayak Nag, Arindam Dutta, Miraj Ahmed, Fahim Faisal Niloy, Amit K. Roy-Chowdhury
Motivated by these, we propose a method for medical image segmentation that adapts to each incoming data batch (online adaptation), incorporates physician feedback through active learning, and assimilates knowledge across facilities in a federated setup.
no code implementations • 24 Dec 2023 • Rohit Lal, Saketh Bachu, Yash Garg, Arindam Dutta, Calvin-Khang Ta, Dripta S. Raychaudhuri, Hannah Dela Cruz, M. Salman Asif, Amit K. Roy-Chowdhury
This challenge arises because these models struggle to generalize beyond their training datasets, and the variety of occlusions is hard to capture in the training data.
no code implementations • 4 Jan 2024 • Sk Miraj Ahmed, Fahim Faisal Niloy, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury
Test time adaptation is the process of adapting, in an unsupervised manner, a pre-trained source model to each incoming batch of the test data (i. e., without requiring a substantial portion of the test data to be available, as in traditional domain adaptation) and without access to the source data.
no code implementations • 6 Jan 2024 • Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy, Basak Guler, Ananthram Swami, Samet Oymak, Amit K. Roy-Chowdhury
Parameter-efficient tuning (PET) methods such as LoRA, Adapter, and Visual Prompt Tuning (VPT) have found success in enabling adaptation to new domains by tuning small modules within a transformer model.
no code implementations • 13 Feb 2024 • Xiangyu Chang, Sk Miraj Ahmed, Srikanth V. Krishnamurthy, Basak Guler, Ananthram Swami, Samet Oymak, Amit K. Roy-Chowdhury
The key premise of federated learning (FL) is to train ML models across a diverse set of data-owners (clients), without exchanging local data.