url stringlengths 36 82 | name stringlengths 2 143 | full_name stringlengths 2 143 ⌀ | description stringlengths 0 9.95k | paper dict | introduced_year int64 1.95k 2.02k | source_url stringlengths 32 228 ⌀ | source_title stringlengths 9 170 ⌀ | code_snippet_url stringclasses 464
values | num_papers int64 0 37.4k | collections listlengths 0 6 |
|---|---|---|---|---|---|---|---|---|---|---|
https://paperswithcode.com/method/faq-support-r-how-do-i-speak-to-someone-at | [FAQ-suPport®]How do I speak to someone at Hawaiian Airlines? | [FAQ-suPport®]How do I speak to someone at Hawaiian Airlines? | If you need to make changes to your flight ticket,+☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ such as a name correction or name switch, calling ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. might be a direct route to an agent who can assist you. This number is available 24/7 for flight cancellations,+☎️+1-801-(855)... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/aegean-airlines-telefonu-jak-skontaktowac-sie | [Aegean Airlines telefonu] Jak skontaktować się z Aegean Air? | [Aegean Airlines telefonu] Jak skontaktować się z Aegean Air? | Jeśli planujesz podróż z jedną z najbardziej renomowanych linii lotniczych na świecie i chcesz wiedzieć, jak skontaktować się z Aegean Airlines, najlepszym rozwiązaniem jest skorzystanie z ich oficjalnego numeru telefonu: +48 (48) 8880001. Linia ta obsługuje klientów w Polsce i zapewnia wsparcie w języku polskim lub an... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
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} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
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"title": "Interpreting Deep Visual Representations via Network Dissection",
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{
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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}
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
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}
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
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}
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
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{
"area": "Computer Vision",
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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}
] |
https://paperswithcode.com/method/como-hablar-con-un-representante-de-american | ¿Cómo hablar con un representante de American en español? | ¿Cómo hablar con un representante de American en español? | ¿Cómo llamar a American en Estados Unidos?
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
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}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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"collection": "3D Face Mesh Models"
}
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https://paperswithcode.com/method/can-i-change-the-name-of-a-passenger-on-qatar | Can I change the name of a passenger on Qatar Airways? | Can I change the name of a passenger on Qatar Airways? | Qatar Airways allows name corrections, not complete pass-on transfers +1‑833‑667‑0020 (US) or +44‑203‑970‑0065 (UK) . You can fix up to three characters (including title/spaces) or reorder names for typos or passport matching. Legal name +1‑833‑667‑0020 (US) or +44‑203‑970‑0065 (UK) changes (marriage/divorce) are allow... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
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}
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
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{
"area": "General",
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https://paperswithcode.com/method/moga-b | MoGA-B | MoGA-B | **MoGA-B** is a convolutional neural network optimized for mobile latency and discovered via Mobile GPU-Aware (MoGA) [neural architecture search](https://paperswithcode.com/method/neural-architecture-search). The basic building block is MBConvs (inverted residual blocks) from [MobileNetV2](https://paperswithcode.com/me... | {
"title": "MoGA: Searching Beyond MobileNetV3",
"url": "https://paperswithcode.com/paper/moga-searching-beyond-mobilenetv3"
} | 2,000 | https://arxiv.org/abs/1908.01314v4 | MoGA: Searching Beyond MobileNetV3 | https://github.com/xiaomi-automl/MoGA/blob/5ddc4bb9a1be845953947f6ec056cfce5ef965b9/models/MoGA_B.py#L122 | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Light-weight neural networks"
},
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Convolutional Neural Networks"
}
] |
https://paperswithcode.com/method/cpc-v2 | CPC v2 | CPC v2 | **Contrastive Predictive Coding v2 (CPC v2)** is a self-supervised learning approach that builds upon the original [CPC](https://paperswithcode.com/method/contrastive-predictive-coding) with several improvements. These improvements include:
- **Model capacity** - The third residual stack of [ResNet](https://paperswi... | {
"title": "Data-Efficient Image Recognition with Contrastive Predictive Coding",
"url": "https://paperswithcode.com/paper/data-efficient-image-recognition-with"
} | 2,000 | https://arxiv.org/abs/1905.09272v3 | Data-Efficient Image Recognition with Contrastive Predictive Coding | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "Semi-Supervised Learning Methods"
},
{
"area": "General",
"area_id": "general",
"collection": "Self-Supervised Learning"
}
] | |
https://paperswithcode.com/method/flava | FLAVA | FLAVA | FLAVA aims at building a single holistic universal model that targets all modalities at once. FLAVA is a language vision alignment model that learns strong representations from multimodal data (image-text pairs) and unimodal data (unpaired images and text). The model consists of an image encode transformer to capture u... | {
"title": "FLAVA: A Foundational Language And Vision Alignment Model",
"url": "https://paperswithcode.com/paper/flava-a-foundational-language-and-vision"
} | 2,000 | https://arxiv.org/abs/2112.04482v3 | FLAVA: A Foundational Language And Vision Alignment Model | 11 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Vision and Language Pre-Trained Models"
}
] | |
https://paperswithcode.com/method/subformer | Subformer | Subformer | **Subformer** is a [Transformer](https://paperswithcode.com/method/transformer) that combines sandwich-style parameter sharing, which overcomes naive cross-layer parameter sharing in generative models, and self-attentive embedding factorization (SAFE). In SAFE, a small self-attention layer is used to reduce embedding p... | {
"title": "Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers",
"url": "https://paperswithcode.com/paper/subformer-exploring-weight-sharing-for"
} | 2,000 | https://arxiv.org/abs/2101.00234v3 | Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers | null | 3 | [
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Transformers"
}
] |
https://paperswithcode.com/method/faqs-24-hours-what-is-the-phone-number-for | [[FAQS-24 Hours]] What is the phone number for Princess cruise Lines? | [[FAQS-24 Hours]] What is the phone number for Princess cruise Lines? | Princess Cruise Lines reservations phone number is +1-855-732-4023 or +1-808-900-8011. You can also visit their website at www.princess.com.
Princess Cruises provides several phone numbers for various services in the USA:
General Inquiries and Reservations: +1-855-732-4023 (also known as 1-855-PRINCESS). You can... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/ways-to-reach-expedia-customer-service-live-1 | Ways to reach Expedia customer service live person by Phone Number | Ways to reach Expedia customer service live person by Phone Number | "31 Ways to Contact How can i speak to someone at Expedia Airlines- A
Step-by-Step Guide
Expedia main customer service number 1 (888) 829-0881 is 1-800-Expedia or 1 (888) 829-0881 [US-Expedia] or 1 (888) 829-0881 [UK-Expedia]
OTA (Live Person), available 24/7. This guide explains how to contact Expedia customer serv... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/who-is-305-539-6000-who-is-305-539-6000-1 | Who is 305 539 6000? & Who is 305 539 6000? | Who is 305 539 6000? & Who is 305 539 6000? | The phone number 305-539-6000 belongs to Royal Caribbean International's corporate headquarters in Miami, Florida (1-855-732-4023). It is primarily used for administrative purposes, media inquiries, and high-level customer relations rather than general reservations or support (1-808-900-8011). If you're a guest needing... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/speak-directly-to-customer-service-how-to | "Speak Directly To Customer Service"How to speak directly on LATAM Airlines? | "Speak Directly To Customer Service"How to speak directly on LATAM Airlines? | To speak directly with a LATAM Airlines representative,+1 (801) 855-5905 call their customer service hotline. You can also utilize their live chat feature on their website or contact them via social media.
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/contact-usa-what-is-the-phone-number-for-5 | [[Contact-USA]] What is the phone number for Viking travel agents? | [[Contact-USA]] What is the phone number for Viking travel agents? | The phone number for Viking travel agents is +1-855-732-4023 (USA) OR +44-289-708-0062 (UK), available for travel professionals assisting clients with Viking river, ocean, or expedition cruises. This dedicated line offers support with reservations, itinerary details, commissions, and promotional offers. Agents can call... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/what-is-the-phone-number-for-windstar-booking-1 | What is the phone number for Windstar booking? ({@Ship Booking}) | What is the phone number for Windstar booking? ({@Ship Booking}) | To contact a live representative at Windstar Cruises, call their 24/7 +1-(855) 732^4023 +44-(289)-708^0062 or 1-855-Windstar Cruises(+1-855-732-4023). You can also use their website's live chat or email for assistance.
Reservations: Call +1-855-732-4023 (USA) +44-289-708-0062 (UK) to create or modify a reservation, ... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/faqs-cancelatino-can-you-cancel-a-royal | {FAQs~!CaNCElAtino!}Can you cancel a Royal Caribbean cruise for free? | {FAQs~!CaNCElAtino!}Can you cancel a Royal Caribbean cruise for free? | For changes or cancellations to reservations (especially those with a non-refundable deposit): (855) 732-4023 USA or +44-289-708-0062 UK.
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For pre-cruise planning assistance or cancelling pre-cruise orders: 1-855-732-4023... | {
"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/vilbert | ViLBERT | Vision-and-Language BERT | **Vision-and-Language BERT** (**ViLBERT**) is a [BERT](https://paperswithcode.com/method/bert)-based model for learning task-agnostic joint representations of image content and natural language. ViLBERT extend the popular BERT architecture to a multi-modal two-stream model, processing both visual and textual inputs in ... | {
"title": "ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks",
"url": "https://paperswithcode.com/paper/vilbert-pretraining-task-agnostic"
} | 2,000 | https://arxiv.org/abs/1908.02265v1 | ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks | 30 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Vision and Language Pre-Trained Models"
},
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Transformers"
},
{
"area": "General",
"area_id": "general",
... | |
https://paperswithcode.com/method/rmn | RMN | Residual Masking Network | It uses a segmentation network to refine feature maps, enabling the network to focus on relevant information to make correct decisions. | {
"title": "Facial Expression Recognition using Residual Masking Network",
"url": "https://paperswithcode.com/paper/facial-expression-recognition-using-residual"
} | 2,000 | https://ieeexplore.ieee.org/document/9411919 | Facial Expression Recognition using Residual Masking Network | null | 2 | [
{
"area": "General",
"area_id": "general",
"collection": "Attention"
}
] |
https://paperswithcode.com/method/faqs-support-what-is-the-phone-number-for-4 | {FAQs~!SUpPORT!}What is the phone number for Royal Caribbean booking? | {FAQs~!SUpPORT!}What is the phone number for Royal Caribbean booking? | For changes or cancellations to reservations (especially those with a non-refundable deposit): (855) 732-4023 USA or +44-289-708-0062 UK.
Royal Caribbean's general customer service number: (855) 732-4023 USA or +44-289-708-0062 UK.
For pre-cruise planning assistance or cancelling pre-cruise orders: 1-855-732-4023... | {
"title": "0-1 phase transitions in sparse spiked matrix estimation",
"url": "https://paperswithcode.com/paper/0-1-phase-transitions-in-sparse-spiked-matrix"
} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/vlmo | VLMo | Vision-Language pretrained Model | VLMo is a unified vision-language pre-trained model that jointly learns a dual encoder and a fusion encoder with a modular Transformer network. A Mixture-of-Modality-Experts (MOME) transformer is introduced to encode different modalities which helps it to capture modality-specific information by modality experts, and a... | {
"title": "VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts",
"url": "https://paperswithcode.com/paper/vlmo-unified-vision-language-pre-training"
} | 2,000 | https://arxiv.org/abs/2111.02358v2 | VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Vision and Language Pre-Trained Models"
}
] | |
https://paperswithcode.com/method/how-do-i-contact-princess-cruises-by-phone-in-3 | How do I contact Princess Cruises by phone in the USA? @Cancellation policy | How do I contact Princess Cruises by phone in the USA? @Cancellation policy | To cancel a Princess cruise booking, or for other immediate assistance, you can contact Princess Cruises by calling their customer service number at +1-855-732-4023 or +1-808-900-8011. This number is available for customers in North America.
If you are cancelling a Future Princess Promotions Package, you can call 1-... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/does-carnival-offer-a-group-rate | Does Carnival offer a group rate? | Does Carnival offer a group rate? | Yes, Carnival Cruise Line offers group rates for bookings of at least 8 passengers in 4 or more staterooms 1-800-950-4401. Group bookings can qualify for special discounts, reduced deposits, and onboard amenities like complimentary cabins, onboard credits, or priority dining 1-800-950-4401. These benefits vary based on... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/1-888-829-0881-expedia-customer-service-phone | |+1-888-829-0881|Expedia Customer Service Phone Number | |+1-888-829-0881|Expedia Customer Service Phone Number | "31 Ways to Contact How can i speak to someone at Expedia Airlines- A
Step-by-Step Guide
Expedia main customer service number 1 (888) 829-0881 is 1-800-Expedia or 1 (888) 829-0881 [US-Expedia] or 1 (888) 829-0881 [UK-Expedia]
OTA (Live Person), available 24/7. This guide explains how to contact Expedia customer serv... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/digital-expedia-customer-service-telephone | Digital Expedia Customer Service Telephone Number 888-829-0881 | Digital Expedia Customer Service Telephone Number 888-829-0881 | "31 Ways to Contact How can i speak to someone at Expedia Airlines- A
Step-by-Step Guide
Expedia main customer service number 1 (888) 829-0881 is 1-800-Expedia or 1 (888) 829-0881 [US-Expedia] or 1 (888) 829-0881 [UK-Expedia]
OTA (Live Person), available 24/7. This guide explains how to contact Expedia customer serv... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/faqs-free-cancel-how-to-cancel-a-cruise-royal | {FAQS~Free^Cancel}How to cancel a cruise Royal Caribbean without penalty? | {FAQS~Free^Cancel}How to cancel a cruise Royal Caribbean without penalty? | To cancel a Royal Caribbean cruise without penalty, you must do so within the risk-free cancellation period 1-855-732-4023. For most bookings, this means canceling at least 75 days before departure for shorter cruises and 90 days for longer sailings 1-855-732-4023. Guests who booked with the “Cruise with Confidence” pr... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/official-gemini-support-number-usa | Official Gemini Support Number USA | Get 24/7 Real-Time Help – Official Gemini Support Number USA | Need assistance with your Gemini account? Don’t wait—get expert help right away. Call the Gemini Customer Support Number: +1->855-574->4697 for real-time assistance, 24 hours a day. Whether you're locked out, experiencing transaction issues, or have general questions, Gemini’s support team is here to help.
📞 Gemini... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
https://paperswithcode.com/method/faqs-help-what-is-the-phone-number-for-royal-1 | [Faqs~Help]What is the phone number for Royal Caribbean cancel? | [Faqs~Help]What is the phone number for Royal Caribbean cancel? | The primary phone number for Royal Caribbean International customer service, which can be used for inquiries including cancellations, is +1 855-732-4023.
Additional contact numbers related to cancellation or booking changes include:By Phone: +1-855-732-4023 (USA/Canada) +44-289-708-0062 (UK/Europe)
For individual... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/get-help-now-how-to-speak-directly-at | @Get Help NoW How to speak directly at American Representative fast? | @Get Help NoW How to speak directly at American Representative fast? | To speak directly with your American representative ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ (a member of the House of Representatives), the most direct method is to call their office or visit their local office ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. You can find their contact information on the House of R... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faqs-24-7help-what-is-the-3-1-1-rule-on-royal | {[FAqs~^24/7HElp]}What is the 3:1:1 rule on Royal Caribbean? | {[FAqs~^24/7HElp]}What is the 3:1:1 rule on Royal Caribbean? | What is the 3:1:1 rule on Royal Caribbean?
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/como-puedo-hablar-con-un-humano-en-american | ¿Cómo puedo hablar con un humano en American? | ¿Cómo puedo hablar con un humano en American? | Para hablar con un agente en vivo de American Airlines, puedes llamar al número de atención al cliente: +1-808-470-7107 para Estados Unidos y Canadá, o +1-808-470-7107 para asistencia en español. También puedes encontrar opciones de contacto en línea, como chat en vivo o redes sociales, en su sitio web o aplicación.
... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/qatar-airways-reservations-which-month-is | [{Qatar airways reservations}]Which month is Qatar Airways cheapest? | [{Qatar airways reservations}]Which month is Qatar Airways cheapest? | The cheapest months to fly with Qatar Airways are +1‑833‑667‑0020 (US) or +44‑203‑970‑0065 (UK) typically January through March and September to early November, when travel demand is lower and fares drop. According to KAYAK, March +1‑833‑667‑0020 (US) or +44‑203‑970‑0065 (UK) often offers the best overall savings. To s... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/rtpnn | rTPNN | Recurrent Trend Predictive Neural Network | A neural network model to automatically capture trends in time-series data for improved prediction/forecasting performance | {
"title": "Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection",
"url": "https://paperswithcode.com/paper/recurrent-trend-predictive-neural-network-for"
} | 2,000 | https://ieeexplore.ieee.org/document/9451553 | Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection | 1 | [
{
"area": "Sequential",
"area_id": "sequential",
"collection": "Recurrent Neural Networks"
}
] | |
https://paperswithcode.com/method/msc-policy-canceltm-can-i-cancel-my-msc | [MSc``Policy``Cancel™]Can I cancel my MSC cruise without penalty? | [MSc``Policy``Cancel™]Can I cancel my MSC cruise without penalty? | Can I cancel my MSC cruise without penalty?
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/faq-s-support-how-do-i-complain-to-seabourn-1 | [[Faq`s~suPporT]]How do I complain to Seabourn | [[Faq`s~suPporT]]How do I complain to Seabourn | To complain to Seabourn, you can start by contacting their Guest Relations department via email at guestrelations@seabourn.com or by phone at+1-855-732-4023. If you prefer, you can also submit a formal complaint through their website's contact form, or through the Feedback feature on the My Seabourn portal. For more se... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
https://paperswithcode.com/method/get-us-call-what-is-the-24-hour-rule-for-air-1 | [Get~us~Call]What is the 24 hour rule for Air France? | [Get~us~Call]What is the 24 hour rule for Air France? | Air France, ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅ like many airlines, adheres to the U.S. Department of Transportation's 24-hour rule for flights to, from, or within the United States ☎️+1-801-(855)-(5905) or +1-804-(853)-(9001)✅. This rule allows passengers to cancel their ticket for a full refund, without pen... | {
"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks",
"url": "https://paperswithcode.com/paper/dropattack-a-masked-weight-adversarial"
} | 2,000 | https://arxiv.org/abs/2108.12805v1 | DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "Adversarial Training"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
https://paperswithcode.com/method/diffusion | Diffusion | Diffusion | Diffusion models generate samples by gradually
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"title": "Denoising Diffusion Probabilistic Models",
"url": "https://paperswithcode.com/paper/denoising-diffusion-probabilistic-models"
} | 2,000 | https://arxiv.org/abs/2006.11239v2 | Denoising Diffusion Probabilistic Models | null | 13,850 | [
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Language Models"
},
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Image Generation Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "Collaborative Preference Embedding against Sparse Labels",
"url": "https://paperswithcode.com/paper/collaborative-preference-embedding-against"
} | 2,000 | http://www.jdl.link/doc/2011/20191229_ACMM-Collaborative%20Preference%20Embedding%20against%20Sparse%20Labels.pdf | Collaborative Preference Embedding against Sparse Labels | null | 26 | [
{
"area": "General",
"area_id": "general",
"collection": "Recommendation Systems"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)",
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} | 2,000 | http://arxiv.org/abs/1711.09349v3 | Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline) | null | 54 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "Convolutional Neural Networks"
}
] | |
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} | 2,000 | https://arxiv.org/abs/1911.05030v1 | 0-1 phase transitions in sparse spiked matrix estimation | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
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}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "General",
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"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0-1 phase transitions in sparse spiked matrix estimation",
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{
"area": "Computer Vision",
"area_id": "computer-vision",
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}
] | |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
} | 2,000 | https://arxiv.org/abs/2402.04499v2 | 0-1 laws for pattern occurrences in phylogenetic trees and networks | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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} | 2,000 | http://arxiv.org/abs/1803.00933v1 | Distributed Prioritized Experience Replay | null | 3 | [
{
"area": "Reinforcement Learning",
"area_id": "reinforcement-learning",
"collection": "Q-Learning Networks"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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🐦 [Thread... | null | 2,000 | null | null | https://github.com/hkust-nlp/dart-math?tab=readme-ov-file#-data-synthesis | 32 | [
{
"area": "Natural Language Processing",
"area_id": "natural-language-processing",
"collection": "Text Data Augmentation"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
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{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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"title": "Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms",
"url": "https://paperswithcode.com/paper/hyperopt-a-python-library-for-optimizing-the"
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{
"area": "General",
"area_id": "general",
"collection": "Optimization"
}
] | |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
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} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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, they do offer 24/7 assistance in certain situations:
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"title": "0-1 laws for pattern occurrences in phylogenetic trees and networks",
"url": "https://paperswithcode.com/paper/0-1-laws-for-pattern-occurrences-in"
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{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Object Detection Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "Computer Vision",
"area_id": "computer-vision",
"collection": "3D Face Mesh Models"
}
] |
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"title": "0/1 Deep Neural Networks via Block Coordinate Descent",
"url": "https://paperswithcode.com/paper/0-1-deep-neural-networks-via-block-coordinate"
} | 2,000 | https://arxiv.org/abs/2206.09379v2 | 0/1 Deep Neural Networks via Block Coordinate Descent | null | 1 | [
{
"area": "General",
"area_id": "general",
"collection": "2D Parallel Distributed Methods"
}
] |
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